Solid-state gas sensors for breath analysis: a review

Human breath analysis; Clinical application and measurement: An overview

Human breath has been recognized as a complex yet predictive mixture of volatile organic compounds (VOCs) and inorganic gas species that can be utilized to non-invasively diagnose common diseases. Current laboratory techniques such as gas chromatography/mass spectrometry (GC/MS) and high-performance liquid chromatography (HPLC), are capable of VOC detection down to ppm concentrations. However, these methods are expensive, non-portable, require pre-processing of the exhaled VOCs, and expert operators, making them unsuitable for wide-spread use. Portable gas sensors have various advantages over other methods used in gas analysis, including ease of transportation, reduced treatment costs, fast results, and improved patient experience. Recent advancements in gas sensing technologies have enabled such devices to be used to diagnose, predict, and monitor a wide range of diseases and conditions, however, many challenges need still need to be addressed (i.e., sensitivity and selectivity) before they can be employed for such applications. Although nanotechnology has greatly improved the performance of gas sensor materials and their capacity to detect VOCs in human breath, issues around repeatability and accuracy remain, as well as adequateness due to the close proximity of the human body and the sensor device. This review focuses on how recent advancements in nanotechnology and solid-state materials have enabled VOC gas sensors to evolve into miniaturized, sensitive and selective devices for monitoring human breath in clinical applications. An introduction to the key aspects of breath analysis, including sources of VOCs in human breath and their role in disease diagnosis, is discussed. Furthermore, the current limitations and future prospects of such gas sensors for breath monitoring applications are also discussed in detail.

Nanomaterial Innovations and Machine Learning in Gas Sensing Technologies for Real-Time Health Diagnostics

Breath sensors represent a frontier in noninvasive diagnostics, leveraging the detection of volatile organic compounds (VOCs) in exhaled breath for real-time health monitoring. This review highlights recent advancements in breath-sensing technologies, with a focus on the innovative materials driving their enhanced sensitivity and selectivity. Polymers, carbon-based materials like graphene and carbon nanotubes, and metal oxides such as ZnO and SnO2 have demonstrated significant potential in detecting biomarkers related to diseases including diabetes, liver/kidney dysfunction, asthma, and gut health. The structural and operational principles of these materials are examined, revealing how their unique properties contribute to the detection of key respiratory gases like acetone, ammonia (NH3), hydrogen sulfide, and nitric oxide. The complexity of breath samples is addressed through the integration of machine learning (ML) algorithms, including convolutional neural networks (CNNs) and support vector machines (SVMs), which optimize data interpretation and diagnostic accuracy. In addition to sensing VOCs, these devices are capable of monitoring parameters such as airflow, temperature, and humidity, essential for comprehensive breath analysis. This review also explores the expanding role of artificial intelligence (AI) in transforming wearable breath sensors into sophisticated tools for personalized health diagnostics, enabling real-time disease detection and monitoring. Together, advances in sensor materials and ML-based analytics present a promising platform for the future of individualized, noninvasive healthcare.

Present and Future of Emerging Catalysts in Gas Sensors for Breath Analysis

To rationalize the noninvasive disease diagnosis by breath analysis, developing a high-performance gas sensor with exceptional sensitivity and selectivity is important to detect trace biomarkers in complex exhaled breath under harsh conditions. Among the various technological innovations, catalyst design and synthesis techniques are the foremost challenges, because gas sensing properties are predominantly determined by surface chemical reactions governed by catalytic activities. Conventional nanoparticle-based catalysts, with their simple structural features, have technical limitations in achieving the requirement for accurate breath analysis. Innovative strategies have been pursued to synthesize unconventional catalyst types with enhanced catalytic capabilities. This Perspective provides a comprehensive overview of recent advancements in catalyst technology for chemiresistive-type gas sensors used in breath analysis. It discusses various emerging catalysts, such as doping catalysts, single-atom catalysts (SACs), bimetallic alloy catalysts, high-entropy alloy (HEA) catalysts, exsolution catalysts, and catalytic filter membranes, along with their unique chemical activation mechanisms that enhance gas sensing properties for detecting target biomarkers in exhaled breath. The review also explores novel strategies for catalyst design, including computational prediction, advanced synthesis techniques, and the integration of sensor arrays with artificial intelligence (AI) to improve diagnostic reliability. By highlighting the crucial role of these emerging catalysts, this review provides valuable insights into the catalytic, synthetic, and analytical aspects that are essential for advancing breath analysis technology.

Rational Design and Application of Breath Sensors for Healthcare Monitoring

Biomarkers contained in human exhaled breath are closely related to certain diseases. As a noninvasive, portable, and efficient health diagnosis method, the breath sensor has received considerable attention in recent years for early disease screening and prevention due to its user-friendly and easy-accessible features. Although some key challenges have been addressed, its capability to precisely monitor specific biomarkers of interest and its physiological relevance to health metrics is still to be ascertained. In this context, we analyzed the rational design and recent advance of breath sensors for healthcare monitoring. This review begins with an introduction to exhaled breath biomarkers and their sensing technologies, such as chemoresistive, humidity-sensitive, electrochemical, and colorimetric principles. Then, a systematic overview of their emerging applications in early disease screening, drunk driving inspection, apnea monitoring, and exhaled breath condensate analysis are demonstrated. Finally, we discuss the challenges and opportunities of breath sensors for noninvasive healthcare monitoring. With the ongoing research efforts, the continuous breakthrough in breath sensors and their attractive applications is foreseeable in the future.

Engineering Nickel(II) Porphyrin-Conjugated Polymers with Different Aryl meso-Substituents for n-Type and p-Type Ammonia Sensors

Conjugated polymers have revolutionized the field of conductometric gas sensors for sensing toxic gases arising from the fast urbanization and industrialization. In this work, we report the synthesis of a series of 5,15-diaryl Ni(II) porphyrin-conjugated polymers (pNiD(Aryl)P) and their integration as the top layer on an octafluorinated copper phthalocyanine (CuF8Pc) sublayer to construct bilayer heterojunction (BLH) devices for ammonia sensing. For the first time, we report the pioneering demonstration of polarity engineering within a BLH device by manipulating the meso-substituent of the 5,15-diaryl Ni(II) porphyrin-conjugated polymer constituting the top layer of the CuF8Pc/pNiD(Aryl)P BLH device. The BLH devices prepared from the 5,15-diaryl Ni(II) porphyrin-conjugated polymer bearing electron-donating meso-substituents as the top layer exhibit a p-type behavior, whereas an n-type behavior is observed for the BLH devices prepared from the 5,15-diaryl Ni(II) porphyrin-conjugated polymer bearing electron-withdrawing meso-substituents. Laser desorption ionization high-resolution mass spectrometry, UV/vis/NIR, and X-ray photoelectron spectroscopy studies provide evidence of a decrease in intramolecular dehydrogenative coupling in pNiD(Aryl)P bearing electron-withdrawing meso-substituents, resulting in low electrical conductivity of the thin films. Density functional theory calculations reveal noninvolvement of electron-withdrawing meso-substituents toward π-delocalization in the fused Ni(II) porphyrin tapes. Interestingly, all the CuF8Pc/pNiD(Aryl)P BLH devices exhibit remarkable sensing response toward NH3. Among all the devices, CuF8Pc/pNiDPP displays the highest sensitivity of -1.17% ppm-1 for NH3, whereas CuF8Pc/pNiDNapP and CuF8Pc/pNiDCNPP exhibit the best limit of detection for NH3, below 200 ppb. In addition, CuF8Pc/pNiDCNPP shows short response and recovery times of 13 and 255 s, respectively, making this device highly suitable for deployment in emergency services.

Unraveling genetic, compositional, and organoleptic traits of elephant garlic of different geographical origins

The ancient native variety of elephant garlic, known as "Aglione della Valdichiana" and cultivated in the Valdichiana area of Tuscany, Italy, has gained recent recognition in the National Catalog of Local Varieties. The renewed interest in traditional products has led to a focus on identifying local varieties of elephant garlic, driven by their distinctive organoleptic and nutritional characteristics. However, other types of elephant garlic nowadays available on the market appear similar, but challenges exist in discerning their origin and composition. This study focused on characterizing elephant garlic from Lazio, Italy, and the Val di Chiana region through genetic, chemical, and aromatic analyses to understand genetic and geographic influences. ISSR markers differentiated elephant garlic from common varieties and highlighted regional genetic diversity. Chemical analysis revealed higher polyphenol content and antioxidant activity in elephant garlic compared to common garlic. Moreover, analysis highlights the variability in the concentrations of sulfur-containing compounds between common and elephant garlic. Aromatic and sensory assessments underscored distinctions between garlic types and regions, emphasizing the significant impact of geographic origin and genetic background on metabolite profiles in Allium genotypes.

Breath Analysis via Gas Chromatography-Mass Spectrometry (GC-MS) in Chronic Coronary Syndrome (CCS): A Proof-of-Concept Study

Background: This proof-of-concept study aimed to assess the diagnostic potential of gas chromatography-mass spectrometry (GC-MS) in profiling volatile organic compounds (VOCs) from exhaled breath as a diagnostic tool for the chronic coronary syndrome (CCS). Methods: Exhaled air was collected from patients undergoing invasive coronary angiography (ICA), with all samples obtained prior to ICA. Post hoc, patients were divided into groups based on coronary lesion severity and indications for revascularization. VOCs in the breath samples were analyzed using GC-MS. Results: This study included 23 patients, of whom 11 did not require myocardial revascularization and 12 did. GC-MS analysis successfully classified 10 of the 11 patients without the need for revascularization (sensitivity of 91%), and 7 of the 12 patients required revascularization (specificity 58%). In subgroup analysis, GC-MS demonstrated 100% sensitivity in identifying patients with significant coronary lesions requiring intervention when the cohort was divided into three groups. A total of 36 VOCs, including acetone, ethanol, and phenol, were identified as distinguishing markers between patient groups. Conclusions: Patients with CCS exhibited a unique fingerprint of exhaled breath, which was detectable with GC-MS. These findings suggest that GC-MS analysis could be a reliable and non-invasive diagnostic tool for CCS. Further studies with larger cohorts are necessary to validate these results and explore the potential integration of VOC analysis into clinical practice.

Rapid differentiation of cystic fibrosis-related bacteria via reagentless atmospheric pressure photoionisation mass spectrometry

Breath analysis is an area of significant interest in medical research as it allows for non-invasive sampling with exceptional potential for disease monitoring and diagnosis. Volatile organic compounds (VOCs) found in breath can offer critical insight into a person's lifestyle and/or disease/health state. To this end, the development of a rapid, sensitive, cost-effective and potentially portable method for the detection of key compounds in breath would mark a significant advancement. Herein, we have designed, built and tested a novel reagent-less atmospheric pressure photoionisation (APPI) source, coupled with mass spectrometry (MS), utilising a bespoke bias electrode within a custom 3D printed sampling chamber for direct analysis of VOCs. Optimal APPI-MS conditions were identified, including bias voltage, cone voltage and vaporisation temperature. Calibration curves were produced for ethanol, acetone, 2-butanone, ethyl acetate and eucalyptol, yielding R2 > 0.99 and limits of detection < 10 pg. As a pre-clinical proof of concept, this method was applied to bacterial headspace samples of Escherichia coli (EC), Pseudomonas aeruginosa (PSA) and Staphylococcus aureus (SA) collected in 1 L Tedlar bags. In particular, PSA and SA are commonly associated with lung infection in cystic fibrosis patients. The headspace samples were classified using principal component analysis with 86.9% of the total variance across the first three components and yielding 100% classification in a blind-sample study. All experiments conducted with the novel APPI arrangement were carried out directly in real-time with low-resolution MS, which opens up exciting possibilities in the future for on-site (e.g., in the clinic) analysis with a portable system.

Electronic Noses: From Gas-Sensitive Components and Practical Applications to Data Processing

Artificial olfaction, also known as an electronic nose, is a gas identification device that replicates the human olfactory organ. This system integrates sensor arrays to detect gases, data acquisition for signal processing, and data analysis for precise identification, enabling it to assess gases both qualitatively and quantitatively in complex settings. This article provides a brief overview of the research progress in electronic nose technology, which is divided into three main elements, focusing on gas-sensitive materials, electronic nose applications, and data analysis methods. Furthermore, the review explores both traditional MOS materials and the newer porous materials like MOFs for gas sensors, summarizing the applications of electronic noses across diverse fields including disease diagnosis, environmental monitoring, food safety, and agricultural production. Additionally, it covers electronic nose pattern recognition and signal drift suppression algorithms. Ultimately, the summary identifies challenges faced by current systems and offers innovative solutions for future advancements. Overall, this endeavor forges a solid foundation and establishes a conceptual framework for ongoing research in the field.

Neonatal Exhaled Breath Sampling for Infrared Spectroscopy: Biomarker Analysis

Monitoring health conditions in neonates for early therapeutic intervention in case deviations from physiological conditions is crucial for their long-term development. Due to their immaturity preterm born neonates are dependent on particularly careful physical and neurological diagnostic methods. Ideally, these should be noninvasive, noncontact, and radiation free. Infrared spectroscopy was used to analyze exhaled breath from 71 neonates with a special emphasis on preterm infants, as a noninvasive, noncontact, and radiation-free diagnostic tool. Passive sample collection was performed by skilled clinicians. Depending on the mode of respiratory support of infants, four different sampling procedures were adapted to collect exhaled breath. With the aid of appropriate reference samples, infrared spectroscopy has successfully demonstrated its effectiveness in the analysis of breath samples of neonates. The discernible increase in concentrations of carbon dioxide, carbon monoxide, and methane in collected samples compared to reference samples served as compelling evidence of the presence of exhaled breath. With regard to technical hurdles and sample analysis, samples collected from neonates without respiratory support proved to be more advantageous compared to those obtained from intubated infants and those with CPAP (continuous positive airway pressure). The main obstacle lies in the significant dilution of exhaled breath in the case of neonates receiving respiratory support. Metabolic analysis of breath samples holds promise for the development of noninvasive biomarker-based diagnostics for both preterm and sick neonates provided an adequate amount of breath is collected.

A Flexible Ammonia Gas Sensor Based on a Grafted Polyaniline Grown on a Polyethylene Terephthalate Film

A novel NH3 gas sensor is introduced, employing polyaniline (PANI) with a unique structure called a graft film. The preparation method was simple: polydopamine (PD) was coated on a flexible polyethylene terephthalate (PET) film and PANI graft chains were grown on its surface. This distinctive three-layer sensor showed a response value of 12 for 50 ppm NH3 in a dry atmosphere at 50 °C. This value surpasses those of previously reported sensors using structurally controlled PANI films. Additionally, it is on par with sensors that combine PANI with metal oxide semiconductors or carbon materials, the high sensitivity of which have been reported. To confirm our film's potential as a flexible sensor, the effect of bending on the its characteristics was investigated. This revealed that although bending decreased the response value, it had no effect on the response time or recovery. This indicated that the sensor film itself was not broken by bending and had sufficient mechanical strength.

Detection of lung cancer and stages via breath analysis using a self-made electronic nose device

BACKGROUND

Breathomics is an emerging area focusing on monitoring and diagnosing pulmonary diseases, especially lung cancer. This research aims to employ metabolomic methods to create a breathprint in human-expelled air to rapidly identify lung cancer and its stages.

RESEARCH DESIGN AND METHODS

An electronic nose (e-nose) system with five metal oxide semiconductor (MOS) gas sensors, a microcontroller, and machine learning algorithms was designed and developed for this application. The volunteers in this study include 114 patients with lung cancer and 147 healthy controls to understand the clinical potential of the e-nose system to detect lung cancer and its stages.

RESULTS

In the training phase, in discriminating lung cancer from controls, the XGBoost classifier model with 10-fold cross-validation gave an accuracy of 91.67%. In the validation phase, the XGBoost classifier model correctly identified 35 out of 42 patients with lung cancer samples and 44 out of 51 healthy control samples providing an overall sensitivity of 83.33% and specificity of 86.27%.

CONCLUSIONS

These results indicate that the exhaled breath VOC analysis method may be developed as a new diagnostic tool for lung cancer detection. The advantages of e-nose based diagnostics, such as an easy and painless method of sampling, and low-cost procedures, will make it an excellent diagnostic method in the future.

π-Extended Porphyrin-Phthalocyanine Heterojunction Devices Exhibiting High Ammonia Sensitivity with a Remarkable Light Effect

π-Extended porphyrins represent an attractive class of organic compounds because of their unique photophysical, optoelectronic, and physicochemical properties. Herein, cross-conjugated (Ace-PQ-Ni) and linear-conjugated (AM6) porphyrins are used to build double-layer heterojunction devices by combining them with a lutetium bisphthalocyanine complex (LuPc2). The heterojunction effect at the porphyrin-phthalocyanine interface plays a key role in the charge transport properties. Both devices exhibit exceptionally high ammonia sensitivity at room temperature and under ambient relative humidity, with limit of detection values of 156 and 115 ppb for Ace-PQ-Ni/LuPc2 and AM6/LuPc2 sensors, respectively. Interestingly, the Ace-PQ-Ni/LuPc2 and AM6/LuPc2 sensors display opposite effects upon light illumination. While the former sensors show largely decreased ammonia sensitivity under light illumination, the current variation of the latter under ammonia is remarkably enhanced with a multiplication factor of 13 and a limit of detection (LOD) of 83 ppb. The striking difference in their sensing properties upon light illumination is attributed to their different π-conjugation pathways (cross-conjugation versus linear conjugation).

In vitro gastrointestinal gas monitoring with carbon nanotube sensors

In vitro simulators of the human gastrointestinal (GI) tract are remarkable technological platforms for studying the impact of food on the gut microbiota, enabling continuous and real-time monitoring of key biomarkers. However, comprehensive real-time monitoring of gaseous biomarkers in these systems is required with a cost-effective approach, which has been challenging to perform experimentally to date. In this work, we demonstrate the integration and in-line use of carbon nanotube (CNT)-based chemiresitive gas sensors coated with a thin polydimethylsiloxane (PDMS) membrane for the continuous monitoring of gases within the Simulator of the Human Microbial Ecosystem (SHIME). The findings demonstrate the ability of the gas sensor to continuously monitor the different phases of gas production in this harsh, anaerobic, highly humid, and acidic environment for a long exposure time (16 h) without saturation. This establishes our sensor platform as an effective tool for real-time monitoring of gaseous biomarkers in in vitro systems like SHIME.

Standard operating procedure to reveal prostate cancer specific volatile organic molecules by infrared spectroscopy

The growing number of prostate cancer cases is a real concern in modern society. Over 1.4 million new cases and about 400 thousand (>26%) deaths were registered worldwide in 2020 due to prostate cancer. The high mortality rate of prostate cancer is due to the lack of reliable early detection of the disease. Till now the most reliable diagnosis of cancer is tissue biopsy, which is an invasive process. A non-invasive or minimally invasive technique could lead to a diagnostic tool that will allow for saving or prolonging the lifespan of millions of lives. Metabolite-based diagnostics may have a better chance of early cancer detection. However, reliable detection techniques need to be developed. Infrared spectroscopy based gaseous-biofluid holds great promise towards the development of non-invasive diagnostics. A pilot study based on breath analysis by infrared spectroscopy showed promising results in distinguishing prostate cancer patients from healthy volunteers. Details of the spectral metabolic analysis are presented.

High-performance pyramid-SiNWs biosensor for NH3gas detection

NH3is widely existed in the environment and is closely associated with various health issues. Additionally, detecting the small amounts of NH3exhaled by patients with liver and kidney diseases offers potential opportunities for painless early disease diagnosis. Therefore, there is an urgent need for a convenient, rapid, and highly sensitive real-time NH3monitoring method. This work presents a high-performance NH3sensor based on olfactory receptor-derived peptides (ORPs) on a pyramid silicon nanowires (SiNWs) structure substrate. First, we successfully fabricated the pyramid-SiNWs structure on a silicon substrate using a chemical etching method. Subsequently, by dehydrative condensation reaction between the amino groups on APTES and the carboxyl groups of ORPs, ORPs were successfully immobilized onto the pyramid-SiNWs structure. This methodology allows the ORPs sensor on the pyramid-SiNWs substrate to detect NH3as low as 1 ppb, which was the reported lowest limit of detection, with a higher response rate compared to ORPs sensors on flat SiNWs substrates. The sensors also exhibit good sensitivity and stability for NH3gas detection. The results show the feasibility and potential applications of ORPs-pyramid-SiNWs structure sensors, in the fields of food safety, disease monitoring, and environmental protection, etc.

Sensitive sensing of Hg(II) based on lattice B and surface F co-doped CeO2: Synergies of catalysis and adsorption brought by doping site engineering

Transition metal oxides are widely used in the detection of heavy metal ions (HMIs), and the co-doping strategy that introducing a variety of different dopant atoms to modify them can obtain a better detection performance. However, there is very little research on the co-doped transition metal oxides by non-metallic elements for electrochemical detection. Herein, boron (B) and fluorine (F) co-doped CeO2 nanomaterial (BFC) is constructed to serve as the electrochemically sensitive interface for the detection of Hg(II). B and F affect the sensitivity of CeO2 to HMIs when they were introduced at different doping sites. Through a variety of characterization, it is proved that B is successfully doped into the lattice and F is doped on the surface of the material. Through the improvement of the catalytic properties and adsorption capacity of CeO2 by different doping sites, this B and F co-doped CeO2 exhibits excellent square wave anodic stripping voltammetry (SWASV) current responses to Hg(II). Both the high sensitivity of 906.99 μA μM-1 cm-2 and the low limit of detection (LOD) of 0.006 μM are satisfactory. Besides, this BFC glassy carbon electrode (GCE) also has good anti-interference property, which has been successfully used in the detection of Hg(II) in actual water. This discovery provides a useful strategy for designing a variety of non-metallic co-doped transition metal oxides to construct trace heavy metal ion-sensitive interfaces.

Research progress of electronic nose technology in exhaled breath disease analysis

Exhaled breath analysis has attracted considerable attention as a noninvasive and portable health diagnosis method due to numerous advantages, such as convenience, safety, simplicity, and avoidance of discomfort. Based on many studies, exhaled breath analysis is a promising medical detection technology capable of diagnosing different diseases by analyzing the concentration, type and other characteristics of specific gases. In the existing gas analysis technology, the electronic nose (eNose) analysis method has great advantages of high sensitivity, rapid response, real-time monitoring, ease of use and portability. Herein, this review is intended to provide an overview of the application of human exhaled breath components in disease diagnosis, existing breath testing technologies and the development and research status of electronic nose technology. In the electronic nose technology section, the three aspects of sensors, algorithms and existing systems are summarized in detail. Moreover, the related challenges and limitations involved in the abovementioned technologies are also discussed. Finally, the conclusion and perspective of eNose technology are presented.

Hollow-Out Fe2O3-Loaded NiO Heterojunction Nanorods Enable Real-Time Exhaled Ethanol Monitoring under High Humidity

The analysis of exhaled breath has opened up new exciting avenues in medical diagnostics, sleep monitoring, and drunk driving detection. Nevertheless, the detection accuracy is greatly affected due to high humidity in the exhaled breath. Here, we propose a regulation method to solve the problem of humidity adaptability in the ethanol-monitoring process by building a heterojunction and hollow-out nanostructure. Therefore, large specific surface area hollow-out Fe₂O₃-loaded NiO heterojunction nanorods assembled by porous ultrathin nanosheets were prepared by a well-tailored interface reaction. The excellent response (51.2 toward 10 ppm ethanol at 80% relative humidity) and selectivity to ethanol under high relative humidity with a lower operating temperature (150 °C) were obtained, and the detection limit was as low as 0.5 ppb with excellent long-term stability. The superior gas-sensing performance was attributed to the high surface activity of the heterojunction and hollow-out nanostructure. More importantly, GC-MS, diffuse reflectance Fourier transform infrared spectroscopy, and DFT were utilized to analyze the mechanisms of heterojunction sensitization, ethanol-sensing reaction, and high-humidity adaptability. Our integrated low-power MEMS Internet of Things (IoT) system based on Fe₂O₃@NiO successfully demonstrates the functional verification of ethanol detection in human exhalation, and the integrated voice alarm and IoT positioning functions are expected to solve the problem of real-time monitoring and rapid initial screening of drunk driving. Overall, this novel method plays a vital role in areas such as control of material morphology and composition, breath analysis, gas-sensing mechanism research, and artificial olfaction.

Non-Invasive Disease Specific Biomarker Detection Using Infrared Spectroscopy: A Review

Many life-threatening diseases remain obscure in their early disease stages. Symptoms appear only at the advanced stage when the survival rate is poor. A non-invasive diagnostic tool may be able to identify disease even at the asymptotic stage and save lives. Volatile metabolites-based diagnostics hold a lot of promise to fulfil this demand. Many experimental techniques are being developed to establish a reliable non-invasive diagnostic tool; however, none of them are yet able to fulfil clinicians' demands. Infrared spectroscopy-based gaseous biofluid analysis demonstrated promising results to fulfil clinicians' expectations. The recent development of the standard operating procedure (SOP), sample measurement, and data analysis techniques for infrared spectroscopy are summarized in this review article. It has also outlined the applicability of infrared spectroscopy to identify the specific biomarkers for diseases such as diabetes, acute gastritis caused by bacterial infection, cerebral palsy, and prostate cancer.

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

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

Highly Sensitive and Selective Gas Sensors Based on NiO/MnO2 @NiO Nanosheets to Detect Allyl Mercaptan Gas Released by Humans under Psychological Stress

NiO nanosheets are synthesized in situ on gas sensor chips using a facile solvothermal method. These NiO nanosheets are then used as gas sensors to analyze allyl mercaptan (AM) gas, an exhaled biomarker of psychological stress. Additionally, MnO₂ nanosheets are synthesized onto the surfaces of the NiO nanosheets to enhance the gas-sensing performance. The gas-sensing response of the NiO nanosheet sensor is higher than that of the MnO₂ @NiO nanosheet sensor. The response value can reach 56.69, when the NiO nanosheet sensor detects 40 ppm AM gas. Interestingly, a faster response time (115 s) is obtained when the MnO₂ @NiO nanosheet sensor is exposed to 40 ppm of AM gas. Moreover, the selectivity toward AM gas is about 17-37 times greater than those toward confounders. The mechanism of gas sensing and the factors contributing to the enhance gas response of the NiO and MnO₂ @NiO nanosheets are discussed. The products of AM gas oxidized by the gas sensor are identified by gas chromatography-mass spectrometry (GC/MS). AM gas detection is an unprecedented application for semiconductor metal oxides. From a broader perspective, the developed sensors represent a new platform for the identification and monitoring of gases released by humans under psychological stress, which is increasing in modern life.

Trends in the Development of Electronic Noses Based on Carbon Nanotubes Chemiresistors for Breathomics

The remarkable potential of breath analysis in medical care and diagnosis, and the consequent development of electronic noses, is currently attracting the interest of the research community. This is mainly due to the possibility of applying the technique for early diagnosis, screening campaigns, or tracking the effectiveness of treatment. Carbon nanotubes (CNTs) are known to be good candidates for gas sensing, and they have been recently considered for the development of electronic noses. The present work has the aim of reviewing the available literature on the development of CNTs-based electronic noses for breath analysis applications, detailing the functionalization procedure used to prepare the sensors, the breath sampling techniques, the statistical analysis methods, the diseases under investigation, and the population studied. The review is divided in two main sections: one focusing on the e-noses completely based on CNTs and one reporting on the e-noses that feature sensors based on CNTs, along with sensors based on other materials. Finally, a classification is presented among studies that report on the e-nose capability to discriminate biomarkers, simulated breath, and animal or human breath.

Study on Ammonia Content and Distribution in the Microenvironment Based on Covalent Organic Framework Nanochannels

A crack-free micrometer-sized compact structure of 1,3,5-tris(4-aminophenyl)benzene-terephthaldehyde-covalent organic frameworks (TAPB-PDA-COFs) was constructed in situ at the tip of a theta micropipette (TMP). The COF-covered theta micropipette (CTP) then created a stable liquid-gas interface inside COF nanochannels, which was utilized to electrochemically analyze the content and distribution of ammonia gas in the microenvironments. The TMP-based electrochemical ammonia sensor (TEAS) shows a high sensing response, with current increasing linearly from 0 to 50,000 ppm ammonia, owing to the absorption of ammonia gas in the solvent meniscus that connects both barrels of the TEAS. The TEAS also exhibits a short response and recovery time of 5 ± 2 s and 6 ± 2 s, respectively. This response of the ammonia sensor is remarkably stable and repeatable, with a relative standard deviation of 6% for 500 ppm ammonia gas dispensing with humidity control. Due to its fast, reproducible, and stable response to ammonia gas, the TEAS was also utilized as a scanning electrochemical microscopy (SECM) probe for imaging the distribution of ammonia gas in a microspace. This study unlocks new possibilities for using a TMP in designing microscale probes for gas sensing and imaging.

A Room-Temperature Surface Acoustic Wave Ammonia Sensor Based on rGO/DPP2T-TT Composite Films

Surface acoustic wave (SAW) sensors based on reduced graphene oxide/poly (diketopyrrolopyrrolethiophene-thieno [3,2-b]thiophene-thiophene) (rGO/DPP2T-TT) composite sensing films for the detection of ammonia were investigated at room temperature in this study. The rGO/DPP2T-TT composite films were deposited onto ST-X quartz SAW resonators by a drop-casting method. FESEM, EDS, and XRD characterizations showed that the rGO/DPP2T-TT composite film was successfully synthesized and exhibited numerous wrinkles and a rough structure, which are crucial for gas adsorption. The frequency response to 500-1400 ppb ammonia shown by the prepared SAW sensor coated with rGO/DPP2T-TT composite film increased linearly as the ammonia concentration increased. The sensor based on a rGO/DPP2T-TT composite film exhibited a positive frequency shift of 55 Hz/ppm, and its frequency response to 500 ppb ammonia was 35 Hz. The sensors thus show promising potential in detecting sub-ppm concentration levels of NH₃ at room temperature, which opens up possibilities for applications in the noninvasive detection of NH₃ in the breath. As a result, the rGO/DPP2T-TT composite sensor can be a good candidate for in situ medical diagnosis and indoor/outdoor environment monitoring.

Heterostructures Based on Cobalt Phthalocyanine Films Decorated with Gold Nanoparticles for the Detection of Low Concentrations of Ammonia and Nitric Oxide

This work is aimed at the development of new heterostructures based on cobalt phthalocyanines (CoPc) and gold nanoparticles (AuNPs), and the evaluation of the prospects of their use to determine low concentrations of ammonia and nitric oxide. For this purpose, CoPc films were decorated with AuNPs by gas-phase methods (MOCVD and PVD) and drop-casting (DC), and their chemiresistive sensor response to low concentrations of NO (10–50 ppb) and NH₃ (1–10 ppm) was investigated. A comparative analysis of the characteristics of heterostructures depending on the preparation methods was carried out. The composition, structure, and morphology of the resulting hybrid films were studied by X-ray photoelectron spectroscopy (XPS) and inductively coupled plasma atomic emission (ICP-AES) spectroscopy, as well as electron microscopy methods to discuss the effect of these parameters on the sensor response of hybrid films to ammonia and nitric oxide. It was shown that regardless of the fabrication method, the response of Au/CoPc heterostructures to NH₃ and NO gases increased with an increase in the concentration of gold. The sensor response of Au/CoPc heterostructures to NH₃ increased 2–3.3 times compared to CoPc film, whereas in the case of NO it increased up to 16 times. The detection limits of the Au/CoPc heterostructure with a gold content of ca. 2.1 µg/cm² for NH₃ and NO were 0.1 ppm and 4 ppb, respectively. It was shown that Au/CoPc heterostructures can be used for the detection of NH₃ in a gas mixture simulating exhaled air (N₂—74%, O₂—16%, H₂O—6%, CO₂—4%).

Preparation of Au@ZnO Nanofilms by Combining Magnetron Sputtering and Post-Annealing for Selective Detection of Isopropanol

We demonstrate the highly sensitive and fast response/recovery gas sensors for detecting isopropanol (IPA), in which the Au-nanoparticles-modified ZnO (Au@ZnO) nanofilms act as the active layers. The data confirm that both the response and the response/recovery speed for the detection of IPA are significantly improved by adding Au nanoparticles on the surface of ZnO nanofilms. The gas sensor with an Optimum Au@ZnO nanofilm exhibits the highest responses of 160 and 7 to the 100 and 1 ppm IPA at 300 °C, which indicates high sensitivity and a very low detecting limit. The sensor also exhibits a very short response/recovery time of 4/15 s on the optimized Au@ZnO nanofilm, which is much shorter than that of the sensor with a pure ZnO nanofilm. The mechanisms of the performance improvement in the sensors are discussed in detail. Both the electronic sensitization and the chemical sensitization of the ZnO nanofilms are improved by the modified Au nanoparticles, which not only regulate the thickness of the depletion layer but also increase the amount of adsorbed oxygen species on the surfaces. This work proposes a strategy to develop a highly sensitive gas sensor for real-time monitoring of IPA.

Designing Cu2+ as a Partial Substitution of Protons in Polyaniline Emeraldine Salt: Room-Temperature-Recoverable H2S Sensing Properties and Mechanism Study

Hydrogen sulfide (H2S) sensors are in urgent demand in the field of hermetic environment detection and metabolic disease diagnosis. However, most of the reported room-temperature (RT) H2S sensors based on transition metal oxides/salts unavoidably suffer from the poisoning effect, resulting in the unrecoverable behavior to restrain their application. Herein, copper(II) chloride-doped polyaniline emeraldine salt (PANI-CuCl2) was devised for RT-recoverable H2S detection, where the copper ion (Cu2+) was designed as a partial substitution of protons (H+) in PANI. The prepared gas sensor exhibited full recovery capability toward 0.25-10 ppm H2S, good repeatability, and long-term stability under 80% RH. Meanwhile, the changes of the PANI-CuCl2 during the H2S sensing period were analyzed via multiple analytical methods to reveal the reversible sensing behavior. Results showed that doping of Cu2+ not only promoted the PANI's response through the formation of conductive copper sulfide (CuS) and following H+ redoping in the PANI but also facilitated the sensor's recovery behavior because of the Cu2+ regeneration under the H+/oxygen environment. This work not only proves the changes of the interaction between the PANI and Cu2+ during the H2S sensing period but also sheds light on designing recoverable H2S sensors based on transition metal salts.

Artificial Olfactory Neuron for an In-Sensor Neuromorphic Nose

A neuromorphic module of an electronic nose (E-nose) is demonstrated by hybridizing a chemoresistive gas sensor made of a semiconductor metal oxide (SMO) and a single transistor neuron (1T-neuron) made of a metal-oxide-semiconductor field-effect transistor (MOSFET). By mimicking a biological olfactory neuron, it simultaneously detects a gas and encoded spike signals for in-sensor neuromorphic functioning. It identifies an odor source by analyzing the complicated mixed signals using a spiking neural network (SNN). The proposed E-nose does not require conversion circuits, which are essential for processing the sensory signals between the sensor array and processors in the conventional bulky E-nose. In addition, they do not have to include a central processing unit (CPU) and memory, which are required for von Neumann computing. The spike transmission of the biological olfactory system, which is known to be the main factor for reducing power consumption, is realized with the SNN for power savings compared to the conventional E-nose with a deep neural network (DNN). Therefore, the proposed neuromorphic E-nose is promising for application to Internet of Things (IoT), which demands a highly scalable and energy-efficient system. As a practical example, it is employed as an electronic sommelier by classifying different types of wines.

Stabilization and Specification in Polymer Field-Effect Transistor Semiconductors

The strong and varied chemical interactions between polymer semiconductors and small molecules, and the electronic consequences of these interactions, make polymer organic field-effect transistors (OFETs) attractive as vapor sensing elements. Two hindrances to their wider acceptance and use are their environmental drift and the poor specificity of individual OFETs. Approaches to addressing these two present drawbacks are presented in this Spotlight on Applications. They include the use of semiconducting polymers with greater inherent stability, circuits that add further stability, and arrays that generate patterns that are much more specific to analyte vapors of interest than the individual responses.

The Combination of Two-Dimensional Nanomaterials with Metal Oxide Nanoparticles for Gas Sensors: A Review

Metal oxide nanoparticles have been widely utilized for the fabrication of functional gas sensors to determine various flammable, explosive, toxic, and harmful gases due to their advantages of low cost, fast response, and high sensitivity. However, metal oxide-based gas sensors reveal the shortcomings of high operating temperature, high power requirement, and low selectivity, which limited their rapid development in the fabrication of high-performance gas sensors. The combination of metal oxides with two-dimensional (2D) nanomaterials to construct a heterostructure can hybridize the advantages of each other and overcome their respective shortcomings, thereby improving the sensing performance of the fabricated gas sensors. In this review, we present recent advances in the fabrication of metal oxide-, 2D nanomaterials-, as well as 2D material/metal oxide composite-based gas sensors with highly sensitive and selective functions. To achieve this aim, we firstly introduce the working principles of various gas sensors, and then discuss the factors that could affect the sensitivity of gas sensors. After that, a lot of cases on the fabrication of gas sensors by using metal oxides, 2D materials, and 2D material/metal oxide composites are demonstrated. Finally, we summarize the current development and discuss potential research directions in this promising topic. We believe in this work is helpful for the readers in multidiscipline research fields like materials science, nanotechnology, chemical engineering, environmental science, and other related aspects.

Role of Working Temperature and Humidity in Acetone Detection by SnO2 Covered ZnO Nanowire Network Based Sensors

A randomly oriented nanowire network, also called nanonet (NN), is a nano-microstructure that is easily integrated into devices while retaining the advantages of using nanowires. This combination presents a highly developed surface, which is promising for sensing applications while drastically reducing integration costs compared to single nanowire integration. It now remains to demonstrate its effective sensing in real conditions, its selectivity and its real advantages. With this work, we studied the feasibility of gaseous acetone detection in breath by considering the effect of external parameters, such as humidity and temperature, on the device’s sensitivity. Here the devices were made of ZnO NNs covered by SnO₂ and integrated on top of microhotplates for the fine and quick control of sensing temperature with low energy consumption. The prime result is that, after a maturation period of about 15 h, the devices are sensitive to acetone concentration as low as 2 ppm of acetone at 370 °C in an alternating dry and wet (50% of relative humidity) atmosphere, even after 90 h of experiments. While still away from breath humidity conditions, which is around 90% RH, the sensor response observed at 50% RH to 2 ppm of acetone shows promising results, especially since a temperature scan allows for ethanol’s distinguishment.

Flexible Ceramic Film Sensors for Free-Form Devices

Recent technological innovations, such as material printing techniques and surface functionalization, have significantly accelerated the development of new free-form sensors for next-generation flexible, wearable, and three-dimensional electronic devices. Ceramic film sensors, in particular, are in high demand for the production of reliable flexible devices. Various ceramic films can now be formed on plastic substrates through the development of low temperature fabrication processes for ceramic films, such as photocrystallization and transferring methods. Among flexible sensors, strain sensors for precise motion detection and photodetectors for biomonitoring have seen the most research development, but other fundamental sensors for temperature and humidity have also begun to grow. Recently, flexible gas and electrochemical sensors have attracted a lot of attention from a new real-time monitoring application that uses human breath and perspiration to accurately diagnose presymptomatic states. The development of a low-temperature fabrication process of ceramic film sensors and related components will complete the chemically stable and reliable free-form sensing devices by satisfying the demands that can only be addressed by flexible metal and organic components.

Simultaneous Biomechanical and Biochemical Monitoring for Self-Powered Breath Analysis

The high moisture level of exhaled gases unavoidably limits the sensitivity of breath analysis via wearable bioelectronics. Inspired by pulmonary lobe expansion/contraction observed during respiration, a respiration-driven triboelectric sensor (RTS) was devised for simultaneous respiratory biomechanical monitoring and exhaled acetone concentration analysis. A tin oxide-doped polyethyleneimine membrane was devised to play a dual role as both a triboelectric layer and an acetone sensing material. The prepared RTS exhibited excellent ability in measuring respiratory flow rate (2-8 L/min) and breath frequency (0.33-0.8 Hz). Furthermore, the RTS presented good performance in biochemical acetone sensing (2-10 ppm range at high moisture levels), which was validated via finite element analysis. This work has led to the development of a novel real-time active respiratory monitoring system and strengthened triboelectric-chemisorption coupling sensing mechanism.

Breath Analysis: A Promising Tool for Disease Diagnosis-The Role of Sensors

Early-stage disease diagnosis is of particular importance for effective patient identification as well as their treatment. Lack of patient compliance for the existing diagnostic methods, however, limits prompt diagnosis, rendering the development of non-invasive diagnostic tools mandatory. One of the most promising non-invasive diagnostic methods that has also attracted great research interest during the last years is breath analysis; the method detects gas-analytes such as exhaled volatile organic compounds (VOCs) and inorganic gases that are considered to be important biomarkers for various disease-types. The diagnostic ability of gas-pattern detection using analytical techniques and especially sensors has been widely discussed in the literature; however, the incorporation of novel nanomaterials in sensor-development has also proved to enhance sensor performance, for both selective and cross-reactive applications. The aim of the first part of this review is to provide an up-to-date overview of the main categories of sensors studied for disease diagnosis applications via the detection of exhaled gas-analytes and to highlight the role of nanomaterials. The second and most novel part of this review concentrates on the remarkable applicability of breath analysis in differential diagnosis, phenotyping, and the staging of several disease-types, which are currently amongst the most pressing challenges in the field.

A Highly Sensitive Ammonia Gas Sensor Using Micrometer-Sized Core-Shell-Type Spherical Polyaniline Particles

A highly sensitive NH₃ gas sensor based on micrometer-sized polyaniline (PANI) spheres was successfully fabricated. The PANI microspheres were prepared via a facile in situ chemical oxidation polymerization in a polystyrene microsphere dispersion solution, resulting in a core–shell structure. The sensor response increased as the diameter of the microspheres increased. The PSt@PANI(4.5) sensor, which had microspheres with a 4.5 μm average diameter, showed the largest response value of 77 for 100 ppm dry NH₃ gas at 30 °C, which was 20 times that of the PANI-deposited film-based sensor. Even considering measurement error, the calculated detection limit was 46 ppb. A possible reason for why high sensitivity was achieved is simply the use of micrometer-sized PANI spherical particles. This research succeeded in providing a new and simple technology for developing a high-sensitivity NH₃ gas sensor that operates at room temperature.

LOX-1 and cancer: an indissoluble liaison

Recently, a strong correlation between metabolic disorders, tumor onset, and progression has been demonstrated, directing new therapeutic strategies on metabolic targets. OLR1 gene encodes the LOX-1 receptor protein, responsible for the recognition, binding, and internalization of ox-LDL. In the past, several studied, aimed to clarify the role of LOX-1 receptor in atherosclerosis, shed light on its role in the stimulation of the expression of adhesion molecules, pro-inflammatory signaling pathways, and pro-angiogenic proteins, including NF-kB and VEGF, in vascular endothelial cells and macrophages. In recent years, LOX-1 upregulation in different tumors evidenced its involvement in cancer onset, progression and metastasis. In this review, we outline the role of LOX-1 in tumor spreading and metastasis, evidencing its function in VEGF induction, HIF-1alpha activation, and MMP-9/MMP-2 expression, pushing up the neoangiogenic and the epithelial-mesenchymal transition process in glioblastoma, osteosarcoma prostate, colon, breast, lung, and pancreatic tumors. Moreover, our studies contributed to evidence its role in interacting with WNT/APC/β-catenin axis, highlighting new pathways in sporadic colon cancer onset. The application of volatilome analysis in high expressing LOX-1 tumor-bearing mice correlates with the tumor evolution, suggesting a closed link between LOX-1 upregulation and metabolic changes in individual volatile compounds and thus providing a viable method for a simple, non-invasive alternative monitoring of tumor progression. These findings underline the role of LOX-1 as regulator of tumor progression, migration, invasion, metastasis formation, and tumor-related neo-angiogenesis, proposing this receptor as a promising therapeutic target and thus enhancing current antineoplastic strategies.

Graphene oxide/polyaniline-based microwave split-ring resonator: A versatile platform towards ammonia sensing

Ammonia gas sensors have always received significant attention as robust platforms for emission control, food safety, and monitoring human exhaled breath for the early diagnosis of diseases such as dysfunction of the kidney and liver. This study explores the development of a microwave-based split-ring resonator (SRR) sensor with enhanced sensitivity to detect ammonia gas at low concentrations. The sensor is based on a nanocomposite fabricated by incorporating 10 wt% of graphene oxide (GO) into polyaniline (PANI) via the in-situ polymerization of aniline monomers over the surface of the GO sheets. The addition of GO to PANI results in a high sensitivity of 0.038 dB ppm^-1 for low concentrations (1-25 ppm) and 0.0045 dB ppm^-1 for high concentrations (> 25 ppm) of ammonia gas, in a 150-400 s time interval at room temperature. The prepared sensor can selectively sense ammonia gas in the presence of other higher concentrations of hazardous gases and a wide range of relative humidity levels (15-90%). The response signal is repeatable after 30 days with less than 0.32% deviation. The developed low-cost and robust sensor has the potential to monitor ammonia gas in various applications, including medical, environmental, food, and agricultural sectors.

Exploring the performance of a functionalized CNT-based sensor array for breathomics through clustering and classification algorithms: from gas sensing of selective biomarkers to discrimination of chronic obstructive pulmonary disease

An array of carbon nanotube (CNT)-based sensors was produced for sensing selective biomarkers and evaluating breathomics applications with the aid of clustering and classification algorithms. We assessed the sensor array performance in identifying target volatiles and we explored the combination of various classification algorithms to analyse the results obtained from a limited dataset of exhaled breath samples. The sensor array was exposed to ammonia (NH₃), nitrogen dioxide (NO₂), hydrogen sulphide (H₂S), and benzene (C₆H₆). Among them, ammonia (NH₃) and nitrogen dioxide (NO₂) are known biomarkers of chronic obstructive pulmonary disease (COPD). Calibration curves for individual sensors in the array were obtained following exposure to the four target molecules. A remarkable response to ammonia (NH₃) and nitrogen dioxide (NO₂), according to benchmarking with available data in the literature, was observed. Sensor array responses were analyzed through principal component analysis (PCA), thus assessing the array selectivity and its capability to discriminate the four different target volatile molecules. The sensor array was then exposed to exhaled breath samples from patients affected by COPD and healthy control volunteers. A combination of PCA, supported vector machine (SVM), and linear discrimination analysis (LDA) shows that the sensor array can be trained to accurately discriminate healthy from COPD subjects, in spite of the limited dataset.

Extensive application of clustering and classification algorithms shows the potential of a CNT-based sensor array in breathomics.

Urine LOX-1 and Volatilome as Promising Tools towards the Early Detection of Renal Cancer

Simple Summary

Renal cell carcinoma (RCC) is often late diagnosed at an advanced stage, worsening the prognosis of the patients. Thus, an early marker is desirable. This paper presents an innovative combined approach useful to identify, for the first time, the presence of LOX-1 protein within the urine of clear cell RCC patients. The LOX-1 protein is related to metabolic disorder-associated carcinogenesis and is shown to be quantitatively correlated to tumor grade and stage. The analysis of volatile compounds released by urine shows the diagnostic potentialities of volatilome and indicates that at least one volatile compound is correlated with both LOX-1 and cancer. In this work, we propose the potential use of a noninvasive approach that enables an early, routine ccRCC diagnosis and leads to a better management of the patients.

Abstract

Renal cell carcinoma (RCC) represents around 3% of all cancers, within which clear cell RCC (ccRCC) are the most common type (70–75%). The RCC disease regularly progresses asymptomatically and upon presentation is recurrently metastatic, therefore, an early method of detection is necessary. The identification of one or more specific biomarkers measurable in biofluids (i.e., urine) by combined approaches could surely be appropriate for this kind of cancer, especially due to easy obtainability by noninvasive method. OLR1 is a metabolic gene that encodes for the Lectin-like oxidized low-density lipoprotein receptor-1 (LOX-1), implicated in inflammation, atherosclerosis, ROS, and metabolic disorder-associated carcinogenesis. Specifically, LOX-1 is clearly involved in tumor insurgence and progression of different human cancers. This work reports for the first time the presence of LOX-1 protein in ccRCC urine and its peculiar distribution in tumoral tissues. The urine samples headspace has also been analyzed for the presence of the volatile compounds (VOCs) by SPME-GC/MS and gas sensor array. In particular, it was found by GC/MS analysis that 2-Cyclohexen-1-one,3-methyl-6-(1-methylethyl)- correlates with LOX-1 concentration in urine. The combined approach of VOCs analysis and protein quantification could lead to promising results in terms of diagnostic and prognostic potential for ccRCC tumors.

Principles of odor coding in vertebrates and artificial chemosensory systems

The biological olfactory system is the sensory system responsible for the detection of the chemical composition of the environment. Several attempts to mimic biological olfactory systems have led to various artificial olfactory systems using different technical approaches. Here we provide a parallel description of biological olfactory systems and their technical counterparts. We start with a presentation of the input to the systems, the stimuli, and treat the interface between the external world and the environment where receptor neurons or artificial chemosensors reside. We then delineate the functions of receptor neurons and chemosensors as well as their overall I-O relationships. Up to this point, our account of the systems goes along similar lines. The next processing steps differ considerably: while in biology the processing step following the receptor neurons is the "integration" and "processing" of receptor neuron outputs in the olfactory bulb, this step has various realizations in electronic noses. For a long period of time, the signal processing stages beyond the olfactory bulb, i.e., the higher olfactory centers were little studied. Only recently there has been a marked growth of studies tackling the information processing in these centers. In electronic noses, a third stage of processing has virtually never been considered. In this review, we provide an up-to-date overview of the current knowledge of both fields and, for the first time, attempt to tie them together. We hope it will be a breeding ground for better information, communication, and data exchange between very related but so far little connected fields.

Sensor array and gas chromatographic detection of the blood serum volatolomic signature of COVID-19

Volatolomics is gaining consideration as a viable approach to diagnose several diseases, and it also shows promising results to discriminate COVID-19 patients via breath analysis. This paper extends the study of the relationship between volatile compounds (VOCs) and COVID-19 to blood serum. Blood samples were collected from subjects recruited at the emergency department of a large public hospital. The VOCs were analyzed with a gas chromatography mass spectrometer (GC/MS). GC/MS data show that in more than 100 different VOCs, the pattern of abundances of 17 compounds identifies COVID-19 from non-COVID with an accuracy of 89% (sensitivity 94% and specificity 83%). GC/MS analysis was complemented by an array of gas sensors whose data achieved an accuracy of 89% (sensitivity 94% and specificity 80%).

Characterization of inflammatory profile by breath analysis in chronic coronary syndromes

AIMS

Exhaled breath contains thousands of volatile organic compounds (VOCs) produced during various metabolic processes both in health and disease.Analysis of breath with electronic nose BIONOTE-V allows modifications of exhaled VOCs to be studied, which are clinically recognized to be a marker for several disorders, including heart failure. New noninvasive tests based on VOCs analysis might be a useful tool for early detection of chronic coronary syndromes (CCS).

METHODS

Exhaled air was collected and measured in individuals with an indication to perform invasive coronary angiography (ICA). All patients' samples were obtained before ICA.

RESULTS

Analysis with BIONOTE-V was performed in a total cohort of 42 patients consecutively enrolled, of whom 19 did not require myocardial revascularization and 23 with indication for myocardial revascularization. BIONOTE-V was able to correctly identify 18 out of 23 patients affected by severe coronary artery disease (sensitivity = 78.3% and specificity = 68.4%). Our predicted model had a tight correlation with SYNTAX score (error of the BIONOTE-V = 15).

CONCLUSION

CCS patients have a distinctive fingerprint of exhaled breath, and analysis by BIONOTE-V has the potential for identifying these patients. Moreover, it seems that this technique can correctly identify patients according to anatomical disease severity at ICA. If the preliminary data of this proof of concept study will be confirmed, this rapid and noninvasive diagnostic tool able to identify CCS might have an impact in routine clinical practice.

The New Approach to a Pattern Recognition of Volatile Compounds: The Inflammation Markers in Nasal Mucus Swabs from Calves Using the Gas Sensor Array

This paper discusses the application of two approaches (direct and inverse) to the identification of volatile substances by means of a gas sensor array in a headspace over nasal mucus swab samples taken from calves with differing degrees of respiratory damage. We propose a unique method to visualize sensor array data for quality analysis, based on the spectra of cross mass sensitivity parameters. The traditional method, which requires an initial sensor array trained on the vapors of the individual substances (database accumulation)—with their further identification in the analyzed bio-samples through the comparison of the analysis results to the database—has shown unsatisfactory performance. The proposed inverse approach is more informative for the pattern recognition of volatile substances in the headspace of mucus samples. The projection of the calculated parameters of the sensor array for individual substances in the principal component space, acquired while processing the sensor array output from nasal swab samples, has allowed us to divide animals into groups according to the clinical diagnosis of their lung condition (healthy respiratory system, bronchitis, or bronchopneumonia). The substances detected in the gas phase of the nasal swab samples (cyclohexanone, butanone-2,4-methyl-2-pentanone) were correlated with the clinical state of the animals, and were consistent with the reference data on disease markers in exhaled air established for destructive organism processes.