Online sample conditioning for portable breath analyzers

Wireless Detection of Trace Ammonia: A Chronic Kidney Disease Biomarker

Elevated levels of ammonia in breath can be linked to medical complications, such as chronic kidney disease (CKD), that disturb the urea balance in the body. However, early stage CKD is usually asymptomatic, and mass screening is hindered by high instrumentation and operation requirements and accessible and reliable detection methods for CKD biomarkers, such as trace ammonia in breath. Enabling methods would have significance in population screening for early stage CKD patients. We herein report a method to effectively immobilize transition metal selectors in close proximity to a single-walled carbon nanotube (SWCNT) surface using pentiptycene polymers containing metal-chelating backbone structures. The robust and modular nature of the pentiptycene metallopolymer/SWCNT complexes creates a platform that accelerates sensor discovery and optimization. Using these methods, we have identified sensitive, selective, and robust copper-based chemiresistive ammonia sensors that display low parts per billion detection limits. We have added these hybrid materials to the resonant radio frequency circuits of commercial near-field communication (NFC) tags to achieve robust wireless detection of ammonia at physiologically relevant levels. The integrated devices offer a noninvasive and cost-effective approach for early detection and monitoring of CKD.

Hydrogel-incorporated Colorimetric Sensors with High Humidity Tolerance for Environmental Gases Sensing

Humidity interferes most gas sensors, especially colorimetric sensors. The conventional approaches to minimize the humidity interference in colorimetric gas sensing require using extra components, causing unwanted analytes loss, or limiting the choices of sensing probes to only hydrophobic ones. To explore the possibility of minimizing the humidity interference in a hydrophilic colorimetric sensing system, we have developed a hydrogel-incorporated approach to buffer the humidity influence on the colorimetric gas sensing. The hydrogel-incorporated colorimetric sensors show not only high humidity tolerance but also the improved analytical performance. The accuracy and reliability of the hydrogel-incorporated colorimetric sensors have also been validated in field tests. This hydrogel-incorporated approach will open up an avenue to implement hydrophilic recipes into colorimetric gas sensors and extend the application of colorimetric sensors to humid gases detection.

Experimental Investigation on Water Adsorption Using Laser Photoacoustic Spectroscopy and Numerical Simulations

In the present research we propose a model to assess the water vapors adsorption capacity of a SiO₂ trap in the breathing circuit, aiming to reduce the loading of interfering compounds in human breath samples. In this study we used photoacoustic spectroscopy to analyze the SiO₂ adsorption of interfering compounds from human breath and numerical simulations to study the flow of expired breath gas through porous media. As a result, the highest adsorption rate was achieved with a flow rate of 300 sccm, while the lowest rate was achieved with a flow rate of 600 sccm. In the procedure of H₂O removal from the human breath air samples, we determined a quantity of 213 cm³ SiO₂ pearls to be used for a 750 mL sampling bag, in order to keep the detection of ethylene free of H₂O interference. The data from this study encourages the premise that the SiO₂ trap is efficient in the reduction of interfering compounds (like water vapors) from the human breath.

Highly selective gas sensing enabled by filters

Portable and inexpensive gas sensors are essential for the next generation of non-invasive medical diagnostics, smart air quality monitoring & control, human search & rescue and food quality assessment to name a few of their immediate applications. Therein, analyte selectivity in complex gas mixtures like breath or indoor air remains the major challenge. Filters are an effective and versatile, though often unrecognized, route to overcome selectivity issues by exploiting additional properties of target analytes (e.g., molecular size and surface affinity) besides reactivity with the sensing material. This review provides a tutorial for the material engineering of sorption, size-selective and catalytic filters. Of specific interest are high surface area sorbents (e.g., activated carbon, silica gels and porous polymers) with tunable properties, microporous materials (e.g., zeolites and metal-organic frameworks) and heterogeneous catalysts, respectively. Emphasis is placed on material design for targeted gas separation, portable device integration and performance. Finally, research frontiers and opportunities for low-cost gas sensing systems in emerging applications are highlighted.

Mitigation of Humidity Interference in Colorimetric Sensing of Gases

Colorimetric sensing technologies have been widely used for both quantitative detection of specific analyte and recognition of a large set of analytes in gas phase, ranging from environmental chemicals to biomarkers in breath. However, the accuracy and reliability of the colorimetric gas sensors are threatened by the humidity interference in different application scenarios. Though substantial progress has been made toward new colorimetric sensors development, unless the humidity interference is well addressed, the colorimetric sensors cannot be deployed for real-world applications. Although there are comprehensive and insightful review articles about the colorimetric gas sensors, they have focused more on the progress in new sensing materials, new sensing systems, and new applications. There is a need for reviewing the works that have been done to solve the humidity issue, a challenge that the colorimetric gas sensors commonly face. In this review paper, we analyzed the mechanisms of the humidity interference and discussed the approaches that have been reported to mitigate the humidity interference in colorimetric sensing of environmental gases and breath biomarkers. Finally, the future perspectives of colorimetric sensing technologies are also discussed.

Colorimetric Sensor for Online Accurate Detection of Breath Acetone

Breath acetone (BrAce) is a validated biomarker of lipid oxidation and has been extensively studied for many applications, such as monitoring ketoacidosis in diabetes, guiding ketogenic diet, and measuring fat burning during exercise. Although many sensors have been reported for BrAce measurement, most of the contributions tested only synthetic or spiked breath samples, because of the complex components of human breath. Here, we show that online accurate detection of BrAce can be achieved using a colorimetric sensor. The high selectivity is enabled by the specific reaction between acetone and hydroxylamine sulfate, and the sensor has a high agreement with a reference instrument in ketosis monitoring. We anticipate that the colorimetric acetone sensor can be applied to various health-related applications.

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.

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

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

Development of a Breath Analyzer for O2 and CO2 Measurement

Background:

Breath analysis can be used to screen disease and detect physical conditions. Many research studies have investigated various sensors or techniques that were used to detect gas concentrations and temperature. However, the studies were less concerned about the performance of sensors.

Methods:

In this study, we developed and tested a portable breath analyzer for exhaled gas measurement. We detected air flow rate, temperature, humidity, CO2 and O2 concentrations. Commercial sensing elements were used to assemble this breath analyzer. All sensors were calibrated to ensure their accuracy. The response times of different sensors were considered. We analyzed breath during three states; 1) seating and resting for 5 min, 2) walking for 5 min and 3) running for 5 min in test participants. Fifteen students 20 to 34 years of age were the test participants.

Results:

Heat, humidity and CO2 production and O2 consumption were calculated from these measured data and were used to assess the performance of the analyzer. The Respiratory Quotient (RQ) were estimated by the ratio of VCO2 to VO2. The RQ values for resting, walking and running states were 0.899, 0.865 and 0.785, respectively. Walking and running significantly increased the heat and humidity production of the human body, corresponding to the human physiological function.

Conclusion:

The RQ value is usually in the range of 0.8 to 0.85. The measurement results for our exhaled analyzer were close to this range. From the respiratory quotient values, the performance of this breath analyzer was reasonable.

Cerium Oxide-Tungsten Oxide Core-Shell Nanowire-Based Microsensors Sensitive to Acetone

Gas sensitive cerium oxide-tungsten oxide core-shell nanowires are synthesized and integrated directly into micromachined platforms via aerosol assisted chemical vapor deposition. Tests to various volatile organic compounds (acetone, ethanol, and toluene) involved in early disease diagnosis demonstrate enhanced sensitivity to acetone for the core-shell structures in contrast to the non-modified materials (i.e., only tungsten oxide or cerium oxide). This is attributed to the high density of oxygen vacancy defects at the shell, as well as the formation of heterojunctions at the core-shell interface, which provide the modified nanowires with ‘extra’ chemical and electronic sensitization as compared to the non-modified materials.

Prospects and Challenges of Volatile Organic Compound Sensors in Human Healthcare

The chemical signatures of volatile organic compounds (VOCs) in humans can be utilized for point-of-care (POC) diagnosis. Apart from toxic exposure studies, VOCs generated in humans can provide insights into one's healthy and diseased metabolic states, acting as a biomarker for identifying numerous diseases noninvasively. VOC sensors and the technology of e-nose have received significant attention for continuous and selective monitoring of various physiological and pathophysiological conditions of an individual. Noninvasive detection of VOCs is achieved from biomatrices of breath, sweat and saliva. Among these, detection from sweat and saliva can be continuous in real-time. The sensing approaches include optical, chemiresistive and electrochemical techniques. This article provides an overview of such techniques. These, however, have limitations of reliability, precision, selectivity, and stability in continuous monitoring. Such limitations are due to lack of sensor stability and complexity of samples in a multivariate environment, which can lead to false readings. To overcome selectivity barriers, sensor arrays enabling multimodal sensing, have been used with pattern recognition techniques. Stability and precision issues have been addressed through advancements in nanotechnology. The use of various forms of nanomaterial not only enhance sensing performance, but also plays a major role in detection on a miniaturized scale. The rapid growth in medical Internet of Things (IoT) and artificial intelligence paves a pathway for improvements in human theranostics.

Toward breath analysis on a chip for disease diagnosis using semiconductor-based chemiresistors: recent progress and future perspectives

Semiconductor gas sensors using metal oxides, carbon nanotubes, graphene-based materials, and metal chalcogenides have been reviewed from the viewpoint of the sensitive, selective, and reliable detection of exhaled biomarker gases, and perspectives/strategies to realize breath analysis on a chip for disease diagnosis are discussed based on the concurrent design of high-performance sensing materials and miniaturized pretreatment components. Carbon-based sensing materials that show relatively high responses to NO and NH₃ at low or mildly raised temperatures can be applied to the diagnosis of asthma and renal disease. Halitosis can be diagnosed by employing sensing or additive materials such as CuO and Mo that have high chemical affinities for H₂S, while catalyst-loaded metal oxide nanostructure sensors or their arrays have been used to diagnose diabetes via the selective detection of acetone or by pattern recognition of sensor signals. For the ultimate miniaturization of a breath-analysis system into a tiny chip, preconditioning that includes preconcentration, dehumidification, and flow sensing needs to be either improved through the design of gas/moisture adsorbents or removed/simplified through the design of highly sensitive sensing materials that are less impervious to interference from humidity and temperature. Moreover, an abundant sensing library needs to be provided for the diagnosis of diseases (e.g. lung cancer) that are associated with multiple biomarker gases and for finding new methods to diagnose other diseases. For this aim, p-type oxide semiconductors with high catalytic activities, as well as combinatorial approaches, can be considered for the development of sensing materials that detect less-reactive large molecules, and high-throughput screening, respectively. Selectivity for a specific biomarker gas will simplify the system further. Breath analysis on a tiny chip using semiconductor chemiresistors with ultralow power consumption that is connected to the 'Internet of Things' will pave new roads for disease diagnosis and patient monitoring.

Assessment, origin, and implementation of breath volatile cancer markers

A new non-invasive and potentially inexpensive frontier in the diagnosis of cancer relies on the detection of volatile organic compounds (VOCs) in exhaled breath samples. Breath can be sampled and analyzed in real-time, leading to fascinating and cost-effective clinical diagnostic procedures. Nevertheless, breath analysis is a very young field of research and faces challenges, mainly because the biochemical mechanisms behind the cancer-related VOCs are largely unknown. In this review, we present a list of 115 validated cancer-related VOCs published in the literature during the past decade, and classify them with respect to their "fat-to-blood" and "blood-to-air" partition coefficients. These partition coefficients provide an estimation of the relative concentrations of VOCs in alveolar breath, in blood and in the fat compartments of the human body. Additionally, we try to clarify controversial issues concerning possible experimental malpractice in the field, and propose ways to translate the basic science results as well as the mechanistic understanding to tools (sensors) that could serve as point-of-care diagnostics of cancer. We end this review with a conclusion and a future perspective.

Detection of volatile organic compounds as biomarkers in breath analysis by different analytical techniques

Breath is a rich mixture containing numerous volatile organic compounds at trace amounts (ppbv–pptv level) such as: hydrocarbons, alcohols, ketones, aldehydes, esters or heterocycles. The presence of some of them depends on health status. Therefore, breath analysis might be useful for clinical diagnostics, therapy monitoring and control of metabolic or biochemical cell cycle products. This Review presents an update on the latest developments in breath analysis applied to diagnosing different diseases with the help of high-quality equipment. Efforts were made to fully and accurately describe traditional and modern techniques used to determine the components of breath. The techniques were compared in terms of design, function and also detection limit of different volatile organic compounds. GC with different detectors, MS, optical sensor and laser spectroscopic detection techniques are also discussed.