Breath ethanol and acetone as indicators of serum glucose levels: an initial report

A comprehensive review on electromagnetic wave based non-invasive glucose monitoring in microwave frequencies

Diabetes is a chronic disease that affects millions of humans worldwide. This review article provides an analysis of the recent advancements in non-invasive blood glucose monitoring, detailing methods and techniques, with a special focus on Electromagnetic wave microwave glucose sensors. While optical, thermal, and electromagnetic techniques have been discussed, the primary emphasis is focussed on microwave frequency sensors due to their distinct advantages. Microwave sensors exhibit rapid response times, require minimal user intervention, and hold potential for continuous monitoring, renders them extremely potential for real-world applications. Additionally, their reduced susceptibility to physiological interferences further enhances their appeal. This review critically assesses the performance of microwave glucose sensors by considering factors such as accuracy, sensitivity, specificity, and user comfort. Moreover, it sheds light on the challenges and upcoming directions in the growth of microwave sensors, including the need for reduction and integration with wearable platforms. By concentrating on microwave sensors within the broader context of non-invasive glucose monitoring, this article aims to offer significant enlightenment that may drive further innovation in diabetes care.

Residential proximity to conventional and unconventional wells and exposure to indoor air volatile organic compounds in the Exposures in the Peace River Valley (EXPERIVA) study

BACKGROUND

In a previous study located in Northeastern British Columbia (Canada), we observed associations between density and proximity of oil and gas wells and indoor air concentrations of certain volatile organic compounds (VOCs). Whether conventional or unconventional well types and phases of unconventional development contribute to these associations remains unknown.

OBJECTIVE

To investigate the associations between proximity-based metrics for conventional and unconventional wells and measured indoor air VOC concentrations in the Exposures in the Peace River Valley (EXPERIVA) study samples.

METHODS

Eighty-four pregnant individuals participated in EXPERIVA. Passive indoor air samplers were analyzed for 47 VOCs. Oil and gas well legacy data were sourced from the British Columbia Energy Regulator. For each participant's home, 5 km, 10 km and no buffer distances were delineated, then density and Inverse Distance Square Weighted (ID2W) metrics were calculated to estimate exposure to conventional and unconventional wells during pregnancy and the VOC measurement period. Multiple linear regression models were used to test for associations between the well exposure metrics and indoor air VOCs. For exposure metrics with >30% participants having a value of 0, we dichotomized exposure (0 vs. >0) and performed ANOVAs to assess differences in mean VOCs concentrations.

RESULTS

Analyses indicated that: 1) conventional well density and ID2W metrics were positively associated with indoor air acetone and decanal; 2) unconventional well density and ID2W metrics were positively associated with indoor air chloroform and decamethylcyclopentasiloxane, and negatively associated with decanal; 3) drilling specific ID2W metrics for unconventional wells were positively associated with indoor air chloroform.

CONCLUSION

Our analysis revealed that the association between the exposure metrics and indoor air acetone could be attributed to conventional wells and the association between exposure metrics and indoor air chloroform and decamethylcyclopentasiloxane could be attributed to unconventional wells.

Non-Invasive Multi-Gas Detection Enabled by Cu-CuO/PEDOT Microneedle Sensor

Metal-oxide-based gas sensors are extensively utilized across various domains due to their cost-effectiveness, facile fabrication, and compatibility with microelectronic technologies. The copper (Cu)-based multifunctional polymer-enhanced sensor (CuMPES) represents a notably tailored design for non-invasive environmental monitoring, particularly for detecting diverse gases with a low concentration. In this investigation, the Cu-CuO/PEDOT nanocomposite was synthesized via a straightforward chemical oxidation and vapor-phase polymerization. Comprehensive characterizations employing X-ray photoelectron spectroscopy (XPS), scanning electron microscopy (SEM), X-ray diffraction (XRD), and micro Raman elucidated the composition, morphology, and crystal structure of this nanocomposite. Gas-sensing assessments of this CuMPES based on Cu-CuO/PEDOT revealed that the response current of the microneedle-type CuMPES surpassed that of the pure Cu microsensor by nearly threefold. The electrical conductivity and surface reactivity are enhanced by poly (3,4-ethylenedioxythiophene) (PEDOT) polymerized on the CuO-coated surface, resulting in an enhanced sensor performance with an ultra-fast response/recovery of 0.3/0.5 s.

α-Fe2O3/TiO2/Ti3C2Tx Nanocomposites for Enhanced Acetone Gas Sensors

Metal oxide semi-conductors are widely applied in various fields due to their low cost, easy processing, and good compatibility with microelectronic technology. In this study, ternary α-Fe2O3/TiO2/Ti3C2Tx nanocomposites were prepared via simple hydrothermal and annealing treatments. The composition, morphology, and crystal structure of the samples were studied using XPS, SEM, EDS, XRD, and multiple other testing methods. The gas-sensing measurement results suggest that the response value (34.66) of the F/M-3 sensor is 3.5 times higher than the pure α-Fe2O3 sensor (9.78) around 100 ppm acetone at 220°C, with a rapid response and recovery time (10/7 s). Furthermore, the sensors have an ultra-low detection limit (0.1 ppm acetone), excellent selectivity, and long-term stability. The improved sensitivity of the composites is mainly attributed to their excellent metal conductivity, the unique two-dimensional layered structure of Ti3C2Tx, and the heterojunction formed between the nanocomposite materials. This research paves a new route for the preparation of MXene derivatives and metal oxide nanocomposites.

Exhaled VOC Biomarkers from Rats Injected with PMs from Thirty-One Major Cities in China

Particulate matter (PMs) of different origins can cause diverse health effects. Here, a homemade box was used to facilitate real-time measurements of breath-borne volatile organic compounds (VOCs) by gas chromatography-ion mobility spectrometry. We have tracked exhaled VOC changes in 228 Wistar rats that were injected with water-soluble PM suspension filtrates (after 0.45 μm) from 31 China cities for 1 h to up to 1-6 days during the experiments. Rats exposed to the filtrates exhibited significant changes in breath-borne VOCs within hours, featuring dynamic fluctuations in the levels of acetone, butan-2-one, heptan-2-one-M, acetic acid-M, and ethanol. Subsequently, on the fifth to sixth day after the injection, there was a notable increase in the proportion of aldehydes (including hexanal-M, hexanal-D, pentanal, heptanal-M, and (E)-2-hexenal). The 10 dynamic VOC fingerprint patterns mentioned earlier showcased the capability to indirectly differentiate urban PM toxicity and categorize the 31 cities into four distinct groups based on their health effects. This study provides valuable insights into the mechanisms of exhaled VOCs and underscores their critical role as biomarkers for differentiating the toxicity of different PMs and detecting the early signs of potential diseases. The results from this work also provide a scientific basis for city-specific air pollution control and policy development.

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

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

Growth of diazonium-functionalized ZnO nanoflakes on flexible carbon cloth for electrochemical sensing of acetone in the liquid phase

Simple detection of acetone is indispensable due to its health and environmental concerns. Surface-modified electrodes are promising for the detection of acetone. In the present study, the facile fabrication of ZnO nanoflakes on carbon cloth (CC) is reported. The electrode was fabricated by decorating the CC with ZnO nanoparticles (ZnO NPs), followed by the hydrothermal treatment and modification with diazonium salt using linear sweep voltammetry (LSV) forming ZnO nanoflakes (ZnO NFs) on ZnO NPs/CC. The as-prepared ZnO/CC electrode was used for the detection of acetone at room temperature using cyclic voltammetry. Fourier transform infrared spectroscopy (FTIR), atomic force microscopy (AFM), scanning electron microscopy (SEM), X-ray diffraction (XRD), and Brunauer-Emmett-Teller (BET) analyses were used for the chemical and physical characterization of the CC before and after each modification step. The obtained data manifested that ZnO NFs functionalized with diazonium salt increased the roughness of the CC surface, which was advantageous to promote the interaction between CC and acetone target. The modified sensing platform showed excellent performance in terms of the wide working range (0.1-2000 ppm) and low detection limit (0.03 ppm), making it a promising and cost-effective sensor of acetone in the liquid phase.

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.

Deep Learning Image Analysis of Nanoplasmonic Sensors: Toward Medical Breath Monitoring

Sensing biomarkers in exhaled breath offers a potentially portable, cost-effective, and noninvasive strategy for disease diagnosis screening and monitoring, while high sensitivity, wide sensing range, and target specificity are critical challenges. We demonstrate a deep learning-assisted plasmonic sensing platform that can detect and quantify gas-phase biomarkers in breath-related backgrounds of varying complexity. The sensing interface consisted of Au/SiO₂ nanopillars covered with a 15 nm metal-organic framework. A small camera was utilized to capture the plasmonic sensing responses as images, which were subjected to deep learning signal processing. The approach has been demonstrated at a classification accuracy of 95 to 98% for the diabetic ketosis marker acetone within a concentration range of 0.5-80 μmol/mol. The reported work provides a thorough exploration of single-sensor capabilities and sets the basis for more advanced utilization of artificial intelligence in sensing applications.

Metabolites From Trypanosome-Infected Cattle as Sensitive Biomarkers for Animal Trypanosomosis

Trypanosomes are important global livestock and human pathogens of public health importance. Elucidating the chemical mechanisms of trypanosome-relevant host interactions can enhance the design and development of a novel, next-generation trypanosomosis diagnostics. However, it is unknown how trypanosome infection affects livestock volatile odors. Here, we show that Trypanosoma congolense and Trypanosoma vivax infections induced dihydro-β- ionone and junenol, while abundance of dihydro-α-ionone, phenolics, p-cresol, and 3-propylphenol significantly elevated in cow urine. These biomarkers of trypanosome infection are conserved in cow breath and the urine metabolites of naturally infected cows, regardless of population, diet, or environment differences. Furthermore, treating trypanosome-infected cows reduced the levels of these indicators back to the pre-infection levels. Finally, we demonstrated that the potential of some specific biomarkers of phenolic origin may be used to detect active trypanosome infections, including low-level infections that are not detectable by microscopy. The sensitivity and specificity of biomarkers detection are suited for rapid, robust, and non-invasive trypanosomosis diagnosis under field conditions.

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 Analysis for the In Vivo Detection of Diabetic Ketoacidosis

Human breath analysis of volatile organic compounds has gained significant attention recently because of its rapid and noninvasive potential to detect various metabolic diseases. The detection of ketones in the breath and blood is key to diagnosing and managing diabetic ketoacidosis (DKA) in patients with type 1 diabetes. It may also be of increasing importance to detect euglycemic ketoacidosis in patients with type 1 or type 2 diabetes or heart failure, treated with sodium-glucose transporter-2 inhibitors (SGLT2-i). The present research evaluates the efficiency of colorimetry for detecting acetone and ethanol in exhaled human breath with the response time, pH effect, temperature effect, concentration effect, and selectivity of dyes. Using the proposed multidye system, we obtained a detection limit of 0.0217 ppm for acetone and 0.029 ppm for ethanol in the detection range of 0.05-50 ppm. A smartphone-assisted unit consisting of a portable colorimetric device was used to detect relative red/green/blue values within 60 s of the interface for practical and real-time application. The developed method could be used for rapid, low-cost detection of ketones in patients with type 1 diabetes and DKA and patients with type 1 or type 2 diabetes or heart failure treated with SGLT2-I and euglycemic ketoacidosis.

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.

Volatolomics in healthcare and its advanced detection technology

Various diseases increasingly challenge the health status and life quality of human beings. Volatolome emitted from patients has been considered as a potential family of markers, volatolomics, for diagnosis/screening. There are two fundamental issues of volatolomics in healthcare. On one hand, the solid relationship between the volatolome and specific diseases needs to be clarified and verified. On the other hand, effective methods should be explored for the precise detection of volatolome. Several comprehensive review articles had been published in this field. However, a timely and systematical summary and elaboration is still desired. In this review article, the research methodology of volatolomics in healthcare is critically considered and given out, at first. Then, the sets of volatolome according to specific diseases through different body sources and the analytical instruments for their identifications are systematically summarized. Thirdly, the advanced electronic nose and photonic nose technologies for volatile organic compounds (VOCs) detection are well introduced. The existed obstacles and future perspectives are deeply thought and discussed. This article could give a good guidance to researchers in this interdisciplinary field, not only understanding the cutting-edge detection technologies for doctors (medicinal background), but also making reference to clarify the choice of aimed VOCs during the sensor research for chemists, materials scientists, electronics engineers, etc.

Functional Microfiber Nonwoven Fabric with Copper Ion-Immobilized Polymer Brush for Detection and Adsorption of Acetone Gas

The detection and removal of volatile organic compounds (VOCs) are emerging as an important problem in modern society. In this study, we attempted to develop a new material capable of detecting or adsorbing VOCs by introducing a new functional group and immobilizing metal ions into a microfiber nonwoven fabric (MNWF) made through radiation-induced graft polymerization. The suitable metal complex was selected according to the data in “Cambridge Crystallographic Data Center (CCDC)”. 4-picolylamine (4-AMP), designated as a ligand through the metal complex data of CCDC, was introduced at an average mole conversion rate of 63%, and copper ions were immobilized at 0.51 mmol/g to the maximum. It was confirmed that degree of grafting (dg) 170% 4-AMP-Cu MNWF, where copper ions are immobilized, can adsorb up to 50% of acetone gas at about 50 ppm, 0.04 mmol/g- 4-AMP-Cu-MNWF, at room temperature and at a ratio of copper ion to adsorbed acetone of 1:10.

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

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

Selectivity of a ZnO@ZIF-71@PDMS Nanorod Array Gas Sensor Enhanced by Coating a Polymer Selective Separation Membrane

It is important for noninvasive diagnosis of diabetes to develop acetone gas sensors with high selectivity. ZnO@ZIF-71 has been reported as a highly sensitive and selective gas sensor on acetone detection. However, it is difficult to exclude the interference with similar molecular sizes gas in the gas-sensing process, like ethanol. To solve this problem, polydimethylsiloxane (PDMS) was synthesized on the surface of ZnO@ZIF-71 to form a ZnO@ZIF-71@PDMS sensor by vapor deposition. The new sensor shows inert response to ethanol and effective response to acetone simultaneously. The PDMS membrane acts as a molecular sieve, which shows the acetone selectivity performance and can totally eliminate the response to low concentration ethanol at low temperature. Theory calculations and solubility test are also employed to prove the role PDMS plays in this process. It demonstrated that the acetone selectivity performance comes from the hydrogen bond interaction between the ethanol gas molecules and PDMS, which increases difficulty for ethanol gas molecules to penetrate the PDMS membrane. Further, this work provides a new method for enhancing gas-sensing selectivity and promoting for miniaturization of gas sensors.

Hypoglycaemia detection and prediction techniques: A systematic review on the latest developments

The main objective of diabetes control is to correct hyperglycaemia while avoiding hypoglycaemia, especially in insulin-treated patients. Fear of hypoglycaemia is a hurdle to effective correction of hyperglycaemia because it promotes under-dosing of insulin. Strategies to minimise hypoglycaemia include education and training for improved hypoglycaemia awareness and the development of technologies to allow their early detection and thus minimise their occurrence. Patients with impaired hypoglycaemia awareness would benefit the most from these technologies. The purpose of this systematic review is to review currently available or in-development technologies that support detection of hypoglycaemia or hypoglycaemia risk, and identify gaps in the research. Nanomaterial use in sensors is a promising strategy to increase the accuracy of continuous glucose monitoring devices for low glucose values. Hypoglycaemia is associated with changes on vital signs, so electrocardiogram and encephalogram could also be used to detect hypoglycaemia. Accuracy improvements through multivariable measures can make already marketed galvanic skin response devices a good noninvasive alternative. Breath volatile organic compounds can be detected by dogs and devices and alert patients at hypoglycaemia onset, while near-infrared spectroscopy can also be used as a hypoglycaemia alarms. Finally, one of the main directions of research are deep learning algorithms to analyse continuous glucose monitoring data and provide earlier and more accurate prediction of hypoglycaemia. Current developments for early identification of hypoglycaemia risk combine improvements of available 'needle-type' enzymatic glucose sensors and noninvasive alternatives. Patient usability will be essential to demonstrate to allow their implementation for daily use in diabetes management.

Recent Trends in Exhaled Breath Diagnosis Using an Artificial Olfactory System

Artificial olfactory systems are needed in various fields that require real-time monitoring, such as healthcare. This review introduces cases of detection of specific volatile organic compounds (VOCs) in a patient's exhaled breath and discusses trends in disease diagnosis technology development using artificial olfactory technology that analyzes exhaled human breath. We briefly introduce algorithms that classify patterns of odors (VOC profiles) and describe artificial olfactory systems based on nanosensors. On the basis of recently published research results, we describe the development trend of artificial olfactory systems based on the pattern-recognition gas sensor array technology and the prospects of application of this technology to disease diagnostic devices. Medical technologies that enable early monitoring of health conditions and early diagnosis of diseases are crucial in modern healthcare. By regularly monitoring health status, diseases can be prevented or treated at an early stage, thus increasing the human survival rate and reducing the overall treatment costs. This review introduces several promising technical fields with the aim of developing technologies that can monitor health conditions and diagnose diseases early by analyzing exhaled human breath in real time.

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.

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.

Fabricating and printing chemiresistors based on monolayer-capped metal nanoparticles

Chemiresistors that are based on monolayer-capped metal nanoparticles (MCNPs) have been used in a wide variety of innovative sensing applications, including detection and monitoring of diagnostic markers in body fluids, explosive materials, environmental contaminations and food quality control. The sensing mechanism is based on reversible swelling or aggregation and/or changes in dielectric constant of the MCNPs. In this protocol, we describe a procedure for producing MCNP-based chemiresistive sensors that is reproducible from device to device and from batch to batch. The approach relies on three main steps: (i) controlled synthesis of gold MCNPs, (ii) fabrication of electrodes that are surrounded with a microbarrier ring to confine the deposited MCNP solution and (iii) a tailor-made drying process to enable evaporation of solvent residues from the MCNP sensing layer to prevent a coffee-ring effect. Application of this approach has been shown to produce devices with ±1.5% variance-a value consistent with the criterion for commercial sensors-as well as long shelf life and stability. Fabrication of chemical sensors based on dodecanethiol- or 2-ethylhexanethiol-capped MCNPs with this approach provides high sensitivity and accuracy in the detection of volatile organic compounds (e.g., octane and decane), toxic gaseous species (e.g., HCl and NH₃) in air and simulated mixtures of lung and gastric cancer from exhaled breath.

Frequency of use of household products containing VOCs and indoor atmospheric concentrations in homes

Volatile organic compounds (VOCs) are a key class of atmospheric emission released from highly complex petrochemical, transport and solvent sources both outdoors and indoors. This study established the concentrations and speciation of VOCs in 60 homes (204 individuals, 360 × 72 h samples, 40 species) in summer and winter, along with outdoor controls. Self-reported daily statistics were collected in each home on the use of cleaning, household and personal care products, all of which are known to release VOCs. Frequency of product use varied widely: deodorants: 2.9 uses home per day; sealant-mastics 0.02 uses home per day. The total concentration of VOCs indoors (range C2-C10) was highly variable between homes e.g. range 16.6-8150 μg m-3 in winter. Indoor concentrations of VOCs exceeded outdoor for 84% of households studied in summer and 100% of homes in winter. The most abundant VOCs found indoors in this study were n-butane (wintertime range: 1.5-4630 μg m-3), likely released as aerosol propellant, ethanol, acetone and propane. The cumulative use VOC-containing products over multiday timescales by occupants provided little predictive power to infer 72 hour averaged indoor concentrations. However, there was weak covariance between the cumulative usage of certain products and individual VOCs. From a domestic emissions perspective, reducing the use of hydrocarbon-based aerosol propellants indoors would likely have the largest impact.

Comprehensive Two-Dimensional Gas Chromatography-Mass Spectrometry Analysis of Exhaled Breath Compounds after Whole Grain Diets

Exhaled breath is a potential noninvasive matrix to give new information about metabolic effects of diets. In this pilot study, non-targeted analysis of exhaled breath volatile organic compounds (VOCs) was made by comprehensive two-dimensional gas chromatography-mass spectrometry (GCxGC-MS) to explore compounds relating to whole grain (WG) diets. Nine healthy subjects participated in the dietary intervention with parallel crossover design, consisting of two high-fiber diets containing whole grain rye bread (WGR) or whole grain wheat bread (WGW) and 1-week control diets with refined wheat bread (WW) before both diet periods. Large interindividual differences were detected in the VOC composition. About 260 VOCs were detected from exhaled breath samples, in which 40 of the compounds were present in more than half of the samples. Various derivatives of benzoic acid and phenolic compounds, as well as some furanones existed in exhaled breath samples only after the WG diets, making them interesting compounds to study further.

Recent Progress in Graphene Derivatives/Metal Oxides Binary Nanocomposites Based Chemi-resistive Sensors for Disease Diagnosis by Breath Analysis

Background::

The scientific and clinical interest of breath analysis for non-invasive disease diagnosis has been focused by the scientific community over the past decade. This was due to the exhalation of prominent volatile organic compounds (VOCs) corresponding to the metabolic activities in the body and their concentration variation. To identify these biomarkers, various analytical techniques have been used in the past and the threshold concentration was established between a healthy and diseased state. Subsequently, various nanomaterials-based gas sensors were explored for their demand in quantifying these biomarkers for real-time, low cost and portable breathalyzers along with the essential sensor performances.

Methods::

We focus on the classification of graphene derivatives and their composites’ gas sensing efficiency for the application in the development of breathalyzers. The review begins with the feasibility of the application of nanomaterial gas sensors for healthcare applications. Then, we systematically report the gas sensing performance of various graphene derivatives/semiconductor metal oxides (SMO) binary nanocomposites and their optimizing strategies in selective detection of biomarkers specific to diseases. Finally, we provide insights on the challenges, opportunity and future research directions for the development of breathalyzers using other graphene derivatives/SMO binary nanocomposites.

Results::

On the basis of these analyses, graphene and its derivatives/metal oxides based binary nanocomposites have been a choice for gas sensing material owing to their high electrical conductivity and extraordinary thickness-dependent physicochemical properties. Moreover, the presence of oxygen vacancies in SMO does not only alter the conductivity but also accelerates the carrier transport rate and influence the adsorption behavior of target analyte on the sensing materials. Hence researchers are exploring the search of ultrathin graphene and metal oxide counterpart for high sensing performances.

Conclusion::

Their impressive properties compared to their bulk counterpart have been uncovered towards sensitive and selective detection of biomarkers for its use in portable breathalyzers.

Adsorption kinetics feature extraction from breathprint obtained by graphene based sensors for diabetes diagnosis

The correlation between blood glucose and breath acetone suggested by several studies has spurred the research community to develop an electronic (e-nose) for diabetes diagnosis. Herein, we have validated the in-house graphene based sensors with known acetone concentration. The sensor performances such as sensitivity, selectivity and stability (SSS) suggested their potential use in acquiring breath print. The 10% higher mean saturation voltage for 30 diabetic subjects ensured a discrimination accuracy of 65% with a positive correlation (r = 0.88) between biochemically measured and non-invasively estimated (glycated haemoglobin) HbA1c. For the improvement of classification rate, thirteen features associated with the adsorption kinetics were extracted from the breathprint from each of the three sensors. The features given as an input to the Naïve Bayes classification model fetched an accuracy of 68.33%. Elimination of redundant features by distinction index and one-R feature ranking algorithm results in Naïve Bayes algorithm with improved performances. The success rate has improved to 70% using the subset of features ranked by one-R algorithm. These results indicated the use of feature ranking algorithms and prediction models for the improvement in accuracy of our in-house fabricated graphene based sensors.

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

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

Skin ethanol gas measurement system with a biochemical gas sensor and gas concentrator toward monitoring of blood volatile compounds

We developed a biochemical gas sensor (bio-sniffer) using the enzymatic reaction of alcohol dehydrogenase (ADH) to target ethanol in skin gas. By introducing a gas concentrator using liquid nitrogen, we constructed a highly sensitive system for skin gas measurements. The ethanol bio-sniffer was built from an optical-fiber probe employing an ADH enzyme membrane, an UV-LED light source for excitation, and a photomultiplier tube. Ethanol was measured by detecting the autofluorescence of the coenzyme NADH due to the enzymatic reaction of ADH. We established a system for measuring concentrated gases by connecting the sensor with a gas concentrator and introducing concentrated skin gas to the sensing surface. This suppressed diffusion of the concentrated gases to achieve maximum fluorescence intensity by optimizing the measurement system. The calibration curve from obtained peak values showed ethanol gas can be measured over 1-3100 ppb, which included skin gas concentrations during alcohol consumption. Finally, when applied to measurements of ethanol in skin gas following alcohol consumption, the output was found to be dependent on concentration, similarly to using standard gases. Consecutive measurements were possible using periodic sampling with 6-min intervals for 180 min of monitoring. Skin ethanol concentrations rose from 20 min after consuming the alcohol, exhibited a peak value of 25 ppb skin gas ethanol at around 60 min, and gradually declined. Thus, the system can be used for non-invasive percutaneous evaluation of human volatile organic chemicals in blood.

Modification of an atmospheric pressure photoionization source for online analysis of exhaled breath coupled with quadrupole time-of-flight mass spectrometry

Breath analysis is a promising method for metabolomics studies and clinical diagnosis, as it enables the observation of metabolites in a convenient and noninvasive way. In this work, an atmospheric pressure photoionization (APPI) source was modified for online analysis of exhaled breath by coupling with quadrupole time-of-flight mass spectrometry (QTOFMS). Three parameters, namely, the capillary voltage, the sampling flow and the curtain gas flow of the APPI source, were optimized. Five healthy volunteers, three males and two females, were enrolled to test the performance of modified APPI-QTOFMS by analyzing their exhaled breath. A total of 21 compounds were tentatively identified, and four metabolites, namely, dimethyl selenoxide, δ-valerolactam, hydroxymandelic acid and palmitic amide were detected in the exhaled breath for the first time. The result shows that modified APPI-QTOFMS can be used for the online study of exhaled breath. Graphical abstract.

Microbiota and Malodor-Etiology and Management

Accumulating evidence indicates that microbiota plays a critical role in physiological processes in humans. However, it might also contribute to body malodor by producing numerous odorous molecules such as ammonia, volatile sulfur compounds or trimethylamine. Although malodor is commonly overlooked by physicians, it constitutes a major problem for many otherwise healthy people. Thus, this review aims to investigate most common causes of malodor and describe potential therapeutic options. We searched PUBMED and Google Scholar databases to identify the clinical and pre-clinical studies on bad body smell, malodor, halitosis and microbiota. Unpleasant smell might originate from the mouth, skin, urine or reproductive fluids and is usually caused by odorants that are produced by resident bacterial flora. The accumulation of odorous compounds might result from diet, specific composition of microbiota, as well as compromised function of the liver, intestines and kidneys. Evidence-based guidelines for management of body malodor are lacking and no universal treatment exists. However, the alleviation of the symptoms may be achieved by controlling the diet and physical elimination of bacteria and/or accumulated odorants.

Review of Non-invasive Glucose Sensing Techniques: Optical, Electrical and Breath Acetone

Annual deaths in the U.S. attributed to diabetes are expected to increase from 280,210 in 2015 to 385,840 in 2030. The increase in the number of people affected by diabetes has made it one of the major public health challenges around the world. Better management of diabetes has the potential to decrease yearly medical costs and deaths associated with the disease. Non-invasive methods are in high demand to take the place of the traditional finger prick method as they can facilitate continuous glucose monitoring. Research groups have been trying for decades to develop functional commercial non-invasive glucose measurement devices. The challenges associated with non-invasive glucose monitoring are the many factors that contribute to inaccurate readings. We identify and address the experimental and physiological challenges and provide recommendations to pave the way for a systematic pathway to a solution. We have reviewed and categorized non-invasive glucose measurement methods based on: (1) the intrinsic properties of glucose, (2) blood/tissue properties and (3) breath acetone analysis. This approach highlights potential critical commonalities among the challenges that act as barriers to future progress. The focus here is on the pertinent physiological aspects, remaining challenges, recent advancements and the sensors that have reached acceptable clinical accuracy.

Pilot Studies of VOC Exposure Profiles during Surgical Operations

Volatile organic chemical exposure resulting from surgical operations is common in operating room personnel. The potential risk of long-term exposure to these low-level chemicals is always a concern. This study was conducted in an area hospital located in northern Taiwan to investigate the internal exposure scenario for operating room personnel. Breath samples were collected before and after surgery, whereas area samples were collected during the surgeries in process. There were 18 volatile organic compounds identified in the samples with gas chromatography-mass spectrometry. The average concentrations of sevoflurane (P = 0.0082), dimethyl sulfide (P = 0.0550), and methyl methacrylate (P = 0.0606) in breath samples collected after surgical operations were significantly higher compared to those obtained before surgical operations, whereas only slight elevations were present for benzene and hexamethyldisiloxane (P < 0.100). In addition, electrosurgical smoke-related chemicals, such as benzene, toluene, ethylbenzene, and m/p-xylene, also presented higher levels in operating room samples compared to the control area. Specifically, the findings in this preliminary study suggested the associations of elevated exposure to sevoflurane across various surgeries to methyl methacrylate with orthopedic surgery and to hexamethyldisiloxane with conventional electrosurgical units. Future study is warranted to explore the short-term high-level chemical exposure in operating rooms and to propose effective preventive measures accordingly to keep any exposure to chemicals at the lowest practical level.

Can oral health and oral-derived biospecimens predict progression of dementia?

Growing evidence indicates that oral health and brain health are interconnected. Declining cognition and dementia coincide with lack of self‐preservation, including oral hygiene. The oral microbiota plays an important role in maintaining oral health. Emerging evidence suggests a link between oral dysbiosis and cognitive decline in patients with Alzheimer's disease. This review showcases the recent advances connecting oral health and cognitive function during aging and the potential utility of oral‐derived biospecimens to inform on brain health. Collectively, experimental findings indicate that the connection between oral health and cognition cannot be underestimated; moreover, oral biospecimens are abundant and readily obtainable without invasive procedures, which may help inform on cognitive health.

Exhaled volatile substances in children suffering from type 1 diabetes mellitus: results from a cross-sectional study

Monitoring metabolic adaptation to type 1 diabetes mellitus in children is challenging. Analysis of volatile organic compounds (VOCs) in exhaled breath is non-invasive and appears as a promising tool. However, data on breath VOC profiles in pediatric patients are limited. We conducted a cross-sectional study and applied quantitative analysis of exhaled VOCs in children suffering from type 1 diabetes mellitus (T1DM) (n = 53) and healthy controls (n = 60). Both groups were matched for sex and age. For breath gas analysis, a very sensitive direct mass spectrometric technique (PTR-TOF) was applied. The duration of disease, the mode of insulin application (continuous subcutaneous insulin infusion vs. multiple daily insulin injection) and long-term metabolic control were considered as classifiers in patients. The concentration of exhaled VOCs differed between T1DM patients and healthy children. In particular, T1DM patients exhaled significantly higher amounts of ethanol, isopropanol, dimethylsulfid, isoprene and pentanal compared to healthy controls (171, 1223, 19.6, 112 and 13.5 ppbV vs. 82.4, 784, 11.3, 49.6, and 5.30 ppbV). The most remarkable differences in concentrations were found in patients with poor metabolic control, i.e. those with a mean HbA1c above 8%. In conclusion, non-invasive breath testing may support the discovery of basic metabolic mechanisms and adaptation early in the progress of T1DM.

Non-Invasive Assessment of Metabolic Adaptation in Paediatric Patients Suffering from Type 1 Diabetes Mellitus

An analysis of exhaled volatile organic compounds (VOC) may deliver systemic information quicker than available invasive techniques. Metabolic aberrations in pediatric type 1 diabetes (T1DM) are of high clinical importance and could be addressed via breathomics. Real-time breath analysis was combined with continuous glucose monitoring (CGM) and blood tests in children suffering from T1DM and age-matched healthy controls in a highly standardized setting. CGM and breath-resolved VOC analysis were performed every 5 minutes for 9 hours and blood was sampled at pre-defined time points. Per participant (n = 44) food intake and physical activity were identical and a total of 22 blood samples and 93 minutes of breath samples were investigated. The inter-individual variability of glucose, insulin, glucagon, leptin, and soluble leptin receptor relative to food intake differed distinctly between patients and controls. In T1DM patients, the exhaled amounts of acetone, 2-propanol, and pentanal correlated to glucose concentrations. Of note, the strength of these correlations strongly depended on the interval between food intake and breath sampling. Our data suggests that metabolic adaptation through postprandial hyperglycemia and related oxidative stress is immediately reflected in exhaled breath VOC concentrations. Clinical translations of our findings may enable point-of-care applicability of online breath analysis towards personalized medicine.

Ultrasensitive Sniff-Cam for Biofluorometric-Imaging of Breath Ethanol Caused by Metabolism of Intestinal Flora

We developed a gas-imaging system (sniff-cam) for gaseous ethanol (EtOH) with improved sensitivity. The sniff-cam was applied to measure the extremely low concentration distribution of breath EtOH without the consumption of alcohol, which is related to the activity of the oral or gut bacterial flora. A ring-type ultraviolet-light-emitting diode was mounted around a camera lens as an excitation light source, which enabled simultaneous excitation and imaging of the fluorescence. In the EtOH sniff-cam, a nicotinamide adenine dinucleotide (NAD)-dependent alcohol dehydrogenase (ADH) was used to catalyze the redox reaction between EtOH and the oxidized form of NAD (NAD⁺). Upon application of gaseous EtOH to the ADH-immobilized mesh that was soaked in an NAD⁺ solution and placed in front of the camera, NADH was produced through an ADH-mediated reaction. NADH expresses fluorescence at an emission wavelength of 490 nm and excitation wavelength of 340 nm. Thus, the concentration distribution of EtOH was visualized by measuring the distribution of the fluorescence light intensity from NADH on the ADH-immobilized mesh surface. First, a comparison of image analysis methods based on the red-green-blue color (RGB) images and the optimization of the buffer pH and NAD⁺ solution concentration was performed. The new sniff-cam showed a 25-fold greater sensitivity and broader dynamic range (20.6-300000 ppb) in comparison to those of the previously fabricated sniff-cam. Finally, we measured the concentration distribution of breath EtOH without alcohol consumption using the improved sniff-cam and obtained a value of 116.2 ± 35.7 ppb (n = 10).

Analysis of Nitrogen-containing Compounds in Mouth-exhaled Breath by Electrospray Ionization Quadrupole Time-of-Flight Mass Spectrometry

Nitrogen-containing compounds are important components in human breath. However, their origins have not yet been clearly understood. In this study, a modified electrospray ionization (ESI) source coupling with quadrupole time-of-flight mass spectrometry has been used for breath analysis. Fourteen nitrogen-containing compounds were identified in mouth-exhaled breath, and 10 of them were from the oral cavity and oropharynx. Moreover, 8 of these nitrogen-containing compounds were recognized as endogenous metabolites. This result provides important clues for exploring the biological origins of these nitrogen-containing compounds. Observation of the ion suppression phenomenon also indicates that breath analysis should be carried out after clearing of the oral cavity and oropharynx, or directly through nose-breathing to eliminate the influence of those nitrogen-containing compounds from the oral cavity.

Microcontroller Implementation of Support Vector Machine for Detecting Blood Glucose Levels Using Breath Volatile Organic Compounds

This paper presents an embedded system-based solution for sensor arrays to estimate blood glucose levels from volatile organic compounds (VOCs) in a patient's breath. Support vector machine (SVM) was trained on a general-purpose computer using an existing SVM library. A training model, optimized to achieve the most accurate results, was implemented in a microcontroller with an ATMega microprocessor. Training and testing was conducted using artificial breath that mimics known VOC footprints of high and low blood glucose levels. The embedded solution was able to correctly categorize the corresponding glucose levels of the artificial breath samples with 97.1% accuracy. The presented results make a significant contribution toward the development of a portable device for detecting blood glucose levels from a patient's breath.

The metabolomic scent of cancer disease progression in soft tissue sarcoma: A case report

BACKGROUND

The purpose of this case report is to describe the potential that metabolomics breath analysis may have in cancer disease monitoring. The advances in mass spectrometry instrumentation allow the accurate real-time analysis of volatile metabolites exhaled in the breath. The application of such non-invasive devices may provide innovative and complementary monitoring of the physio-pathological conditions of cancer patients.

CASE PRESENTATION

A 59-year-old Caucasian woman with spindle cell malignant mesenchymal sarcoma of the presacral region started a first-line therapy with non-pegylated liposomal doxorubicin and ifosfamide associated with pelvic radiant treatment. After two cycles of chemotherapy plus radiotherapy, a significant pulmonary disease progression was reported. Thus, a second-line therapy with trabectedin was administered. However, after only two cycles of treatment a re-staging computed tomography scan reported further cancer disease progression of the target pulmonary lesions as well as occurrence of new satellite bilateral nodules. Real-time analysis of breath exhaled volatile organic compounds, performed by select ion flow tube mass spectrometry (SIFT-MS) during the follow-up of the patient, showed a specific metabolic pattern not observed in the breath of other soft tissue sarcoma patients who achieved clinical benefit from the treatments.

CONCLUSIONS

This case report revealed the importance of the non-invasive real-time volatile organic compounds breath analysis to distinguish individual specific chemo-resistance phenotypes among soft tissue sarcoma patients. Such observation seems to suggest that breath metabolomics may be particularly useful for monitoring cancer disease progression in soft tissue sarcoma patients where only cost-effective diagnostic tools, such as positron emission tomography and computed tomography, are available.

Ion mobility spectrometry: the diagnostic tool of third millennium medicine

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

Radio-Frequency and Microwave Techniques for Non-Invasive Measurement of Blood Glucose Levels

This paper reviews non-invasive blood glucose measurements via dielectric spectroscopy at microwave frequencies presented in the literature. The intent is to clarify the key challenges that must be overcome if this approach is to work, to suggest some possible ways towards addressing these challenges and to contribute towards prevention of unnecessary ‘reinvention of the wheel’.

ZIF Nanocrystal-Based Surface Acoustic Wave (SAW) Electronic Nose to Detect Diabetes in Human Breath

In the present work, a novel, portable and innovative eNose composed of a surface acoustic wave (SAW) sensor array based on zeolitic imidazolate frameworks, ZIF-8 and ZIF-67 nanocrystals (pure and combined with gold nanoparticles), as sensitive layers has been tested as a non-invasive system to detect different disease markers, such as acetone, ethanol and ammonia, related to the diagnosis and control of diabetes mellitus through exhaled breath. The sensors have been prepared by spin coating, achieving continuous sensitive layers at the surface of the SAW device. Low concentrations (5 ppm, 10 ppm and 25 ppm) of the marker analytes were measured, obtaining high sensitivities, good reproducibility, short time response and fast signal recovery.

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

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

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

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