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

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

The Detection of Colorectal Cancer through Machine Learning-Based Breath Sensor Analysis.

Colorectal cancer (CRC) is the third most common malignancy and the second most common cause of cancer-related deaths worldwide. While CRC screening is already part of organized programs in many countries, there remains a need for improved screening tools. In recent years, a potential approach for cancer diagnosis has emerged via the analysis of volatile organic compounds (VOCs) using sensor technologies. The main goal of this study was to demonstrate and evaluate the diagnostic potential of a table-top breath analyzer for detecting CRC. Breath sampling was conducted and CRC vs. non-cancer groups (105 patients with CRC, 186 non-cancer subjects) were included in analysis. The obtained data were analyzed using supervised machine learning methods (i.e., Random Forest, C4.5, Artificial Neural Network, and Naïve Bayes). Superior accuracy was achieved using Random Forest and Evolutionary Search for Features (79.3%, sensitivity 53.3%, specificity 93.0%, AUC ROC 0.734), and Artificial Neural Networks and Greedy Search for Features (78.2%, sensitivity 43.3%, specificity 96.5%, AUC ROC 0.735). Our results confirm the potential of the developed breath analyzer as a promising tool for identifying and categorizing CRC within a point-of-care clinical context. The combination of MOX sensors provided promising results in distinguishing healthy vs. diseased breath samples. Its capacity for rapid, non-invasive, and targeted CRC detection suggests encouraging prospects for future clinical screening applications.

SARS CoV-2 infection screening via the exhaled breath fingerprint obtained by FTIR spectroscopic gas-phase analysis. A proof of concept.

The COVID-19 pandemic remains a global challenge now with the long-COVID arising. Mitigation measures focused on case counting, assessment and determination of variants and their likely targets of infection and transmission, the pursuit of drug treatments, use and enhancement of masks, social distancing, vaccination, post-infection rehabilitation, and mass screening. The latter is of utmost importance given the current scenario of infections, reinfections, and long-term health effects. Research on screening platforms has been developed to provide more sensitive, specific, and reliable tests that are accessible to the entire population and can be used to assess the prognosis of the disease as well as the subsequent health follow-up of patients with sequelae of COVID-19. Therefore, the aim of the present study was the simulation of exhaled breath of COVID-19 patients by evaluation of three identified COVID-19 indicator breath biomarkers (acetone (ACE), acetaldehyde (ACH) and nitric oxide (NO)) by gas-phase infrared spectroscopy as a proof-of-concept principle for the detection of infected patients' exhaled breath fingerprint and subsequent follow-up. The specific fingerprints of each of the compounds and the overall fingerprint were obtained. The synthetic exhaled breath evaluation concept revealed a linearity of r = 0.99 for all compounds, and LODs of 6.42, 13.81, 9.22 ppm, and LOQs of 42.26, 52.57, 69.23 ppm for NO, ACE, and ACH, respectively. This study proves the fundamental feasibility of gas-phase infrared spectroscopy for fingerprinting lung damage biomarkers in exhaled breath of patients with COVID-19. This analysis would allow faster and cheaper screening and follow-up of infected individuals, which could improve mass screening in POC settings.

Modular Breath Analyzer (MBA): Introduction of a Breath Analyzer Platform Based on an Innovative and Unique, Modular eNose Concept for Breath Diagnostics and Utilization of Calibration Transfer Methods in Breath Analysis Studies.

Exhaled breath analysis for early disease detection may provide a convenient method for painless and non-invasive diagnosis. In this work, a novel, compact and easy-to-use breath analyzer platform with a modular sensing chamber and direct breath sampling unit is presented. The developed analyzer system comprises a compact, low volume, temperature-controlled sensing chamber in three modules that can host any type of resistive gas sensor arrays. Furthermore, in this study three modular breath analyzers are explicitly tested for reproducibility in a real-life breath analysis experiment with several calibration transfer (CT) techniques using transfer samples from the experiment. The experiment consists of classifying breath samples from 15 subjects before and after eating a specific meal using three instruments. We investigate the possibility to transfer calibration models across instruments using transfer samples from the experiment under study, since representative samples of human breath at some conditions are difficult to simulate in a laboratory. For example, exhaled breath from subjects suffering from a disease for which the biomarkers are mostly unknown. Results show that many transfer samples of all the classes under study (in our case meal/no meal) are needed, although some CT methods present reasonably good results with only one class.

An eNose-based method performing drift correction for online VOC detection under dry and humid conditions.

Our recently demonstrated innovative concept of electronic nose (eNose) based on a combination of gas sensors is further tested and benchmarked in the present study. The system is a test bed for gas sensors of different principal technologies distributed within three compartments, which share a compact, very low volume, temperature-controlled sensing chamber. Here, the eNose-based analyser contains three sensing arrays of commercially available semiconducting metal oxide (MOX) gas sensors: one compartment contains 8 analog MOX sensors, while the other two compartments comprise 10 digital MOX sensors. The presented instrument is explicitly tested for the discrimination between mid-range (3-18 ppm) concentrations of different volatile organic compounds (VOCs) including acetaldehyde, acetone, ethanol, ethyl acetate, isoprene and n-pentane under dry and humid conditions, which are all considered relevant gases in future breath diagnostic applications. Since the experiments were performed in periods of time separated by around 20 days, they are affected by drift. For this reason, we explore the opportunity of drift mitigation using methods based on component removal computed by linear discriminant analysis, partial least squares discriminant analysis and direct orthogonalization, which lend themselves to future in-field applications of the developed device and sensing methodology.

Characterization of metal oxide gas sensors via optical techniques.

Metal oxide (MOX) sensors are increasingly gaining attention in analytical applications. Their fundamental operation principle is based on conversion reactions of selected molecular species at their semiconducting surface. However, the exact turnover of analyte gas in relation to the concentration has not been investigated in detail to date. In the present study, two optical sensing techniques-luminescence quenching for molecular oxygen and infrared spectroscopy for carbon dioxide and methane-have been coupled for characterizing the behavior of an example semiconducting MOX methane gas sensor integrated into a recently developed low-volume gas cell. Thereby, oxygen consumption during MOX operation as well as the generation of carbon dioxide from the methane conversion reaction could be quantitatively monitored. The latter was analyzed via a direct mid-infrared gas sensor system based on substrate-integrated hollow waveguide (iHWG) technology combined with a portable Fourier transform infrared spectrometer, which has been able to not only detect the amount of generated carbon dioxide but also the consumption of methane during MOX operation. Hence, a method based entirely on direct optical detection schemes was developed for characterizing the actual signal generating processes-here for the detection of methane-via MOX sensing devices via near real-time online analysis. Graphical Abstract.

iHWG-MOX: A Hybrid Breath Analysis System via the Combination of Substrate-Integrated Hollow Waveguide Infrared Spectroscopy with Metal Oxide Gas Sensors.

According to their materials and operating parameters, metal oxide (MOX) sensors respond to target gases only by a change in sensor resistance with a lack in selectivity. By the use of infrared spectroscopy, highly discriminatory information from samples at a molecular level can be obtained and the selectivity can be enhanced. A low-volume gas cell was developed for a commercially available semiconducting MOX methane gas sensor and coupled directly to a mid-infrared gas sensor based on substrate-integrated hollow waveguide (iHWG) technology combined with a Fourier transform infrared spectrometer. This study demonstrates a sensing process with combined orthogonal sensors for fast, time-resolved, and synergic detection of methane and carbon dioxide in gas samples.

An Innovative Modular eNose System Based on a Unique Combination of Analog and Digital Metal Oxide Sensors.

An innovative concept for an electronic nose (eNose) system based on a unique combination of analog and digital sensors for online monitoring is presented. The developed system consists of small sensing arrays of commercially available semiconducting metal oxide (MOX) gas sensors in a compact, modular, low sample volume, temperature-controlled sensing chamber. The sensing chamber comprises three compartments, each of which may contain several analog and/or digital MOX sensors. Additional sensors within the digital compartment allow for pressure, humidity, and temperature measurements. The presented prototype eNose system comprises one compartment with 8 analog MOX sensors and two compartments with 10 digital sensors each and was explicitly tested here for the discrimination between midrange (3-18 ppm) concentrations of ethanol and acetone at dry and moderately humid conditions.

Expansion of the scope of alkylboryl-bridged N → B-ladder boranes: new substituents and alternative substrates.

A series of new boranes capable of forming intramolecular N → B-heterocycles has been prepared and their properties have been studied by electrochemical methods and UV-vis-spectroscopy complemented by DFT calculations. A dimethylborane (BMe2), haloborane derivatives (BBr2, BF2, BI2) and mixed cyano/isocyano-borane (B(CN)(NC)) have been prepared by different techniques. Furthermore, 2'-alkynyl-substituted 2-phenylpyridines bearing terminal tert-butyl- and trimethylsilyl-groups are introduced as a new class of substrates for hydroboration. Successful hydroboration with either 9H-borabicyclo[3.3.1]-nonane (9H-BBN), dimesitylborane (Mes2B-H), or Piers' borane ((C6F5)2B-H, BPF-H) furnished new π-extended boranes capable of forming intramolecular six- or seven-membered N → B-heterocycles (tBuBBN, SiBPF), and, in the case of Mes2BH, formation of a sterically crowded styrylborane (SiBMes2) incapable of intramolecular N → B-coordination was observed. All the boranes listed above except BMe2 have been structurally characterized, and a study of their electrochemical properties showed that the systematic variation of the substituents on boron allows for the incremental variation of the electron affinity of the phenylpyridine-model system over a total range of >0.7 eV between alkylboranes (BMe2, BBN) and B(CN)(NC). B(CN)(NC) shows the strongest N → B-bond (≈175 kJ mol-1), and highest electron-affinity observed so far, and is the first example of a borane bearing an isocyano-substituent on boron.