Lung cancer identification by the analysis of breath by means of an array of non-selective gas sensors

Previous finding shown that the composition of the breath of patients with lung cancer contains information that could be used to detect the disease. These volatiles are mainly alkanes and aromatic compounds. Sensor arrays technology (electronic nose) proved to be useful to screen samples characterised by different headspace composition. Here we investigated the possibility of using an electronic nose to check whether volatile compounds present in expired air may diagnose lung cancer. Breath samples were collected and immediately analysed by an electronic nose. A total of 60 individuals were involved in the experiment. 35 of them were affected by lung cancer, 18 individuals were measured as reference and nine were measured after the surgical therapy. Two individuals were measured twice, before and after the surgical therapy, for a total of 62 measurements. An electronic nose, composed by eight quartz microbalance (QMB) gas sensors, coated with different metalloporphyrins, was used. These sensors show a good sensitivity towards those compounds previously indicated as possible lung cancer markers in breath. The application of a 'partial least squares-discriminant analysis' (PLS-DA) found out a 100% of classification of lung cancer affected patients, 94% of reference was correctly classified. The class of post-surgery patients were correctly individuated in 44% of the cases, while the other samples were classified as healthy references. The alteration of breath composition induced by the presence of lung cancer was enough to allow a complete identification of the sample of diseased individuals. Extended studies are necessary to evaluate the resolution of the method, namely the stage at which the disease may be identified in order to use this instrument for early diagnosis.     

Monitoring growth of the methanogenic archaea Methanobacterium formicicum using an electronic nose

Growth of the methanogenic archaea, Methanobacterium formicicum, in pure culture was monitored by analysing samples from the gas phase with an array of chemical gas sensors (an `electronic nose'). Analyses of the methane and protein formation rates were used as independent parameters of growth, and the data obtained from the electronic nose were evaluated using principal component analysis (PCA). We found that different growth phases can be distinguished with the electronic nose followed by PCA evaluation. The fast response of the sensors in combination with the high correlations with other parameters measuring growth show that the electronic nose can be a useful tool to rapidly determine methanogenic growth.     

Bacteria classification using Cyranose 320 electronic nose

Background  

An electronic nose (e-nose), the Cyrano Sciences' Cyranose 320, comprising an array of thirty-two polymer carbon black composite sensors has been used to identify six species of bacteria responsible for eye infections when present at a range of concentrations in saline solutions. Readings were taken from the headspace of the samples by manually introducing the portable e-nose system into a sterile glass containing a fixed volume of bacteria in suspension. Gathered data were a very complex mixture of different chemical compounds.     

Use of an electronic nose system for diagnoses of urinary tract infections

The use of volatile production patterns produced by bacterial contaminants in urine samples were examined using electronic nose technology. In two experiments 25 and 45 samples from patients were analysed for specific bacterial contaminants using agar culture techniques and the major UTI bacterial species identified. These samples were also analysed by incubation in a volatile generation test tube system for 4-5 h. The volatile production patterns were then analysed using an electronic nose system with 14 conducting polymer sensors. In the first experiment analysis of the data using a neural network (NN) enabled identification of all but one of the samples correctly when compared to the culture information. Four groups could be distinguished, i.e. normal urine, Escherichia coli infected, Proteus spp. and Staphylococcus spp. In the second experiment it was again possible to use NN systems to examine the volatile production patterns and identify 18 of 19 unknown UTI cases. Only one normal patient sample was mis-identified as an E. coli infected sample. Discriminant function analysis also differentiated between normal urine samples, that infected with E. coli and with Staphylococcus spp. This study has shown the potential for early detection of microbial contaminants in urine samples using electronic nose technology for the first time. These findings will have implications for the development of rapid systems for use in clinical practice.     

The use of gas-sensor arrays to diagnose urinary tract infections

Sensorial analysis based on the utilisation of human senses, is one of the most important and straightforward investigation methods in food and chemical analysis. An electronic nose has been used to detect in vivo Urinary Tract Infections from 45 suspected cases that were sent for analysis in a UK Health Laboratory environment. These samples were analysed by incubation in a volatile generation test tube system for 4-5 h. The volatile production patterns were then analysed using an electronic nose system with 14 conducting polymer sensors. An intelligent model consisting of an odour generation mechanism, rapid volatile delivery and recovery system, and a classifier system based on learning techniques has been considered. The implementation of an Extended Normalised Radial Basis Function network with advanced features for determining its size and parameters and the concept of fusion of multiple classifiers dedicated to specific feature parameters has been also adopted in this study. The proposed scheme achieved a very high classification rate of the testing dataset, demonstrating in this way the efficiency of the proposed scheme compared with other approaches. This study has shown the potential for early detection of microbial contaminants in urine samples using electronic nose technology.     

Monitoring haemodialysis using electronic nose and chemometrics

An ever-increasing number of patients have to undergo regular renal dialysis to compensate for acute or chronic renal failure. The adequacy of the treatment has a profound effect on patients’ morbidity and mortality. Therefore, it is necessary to assess the delivered dialysis dose. For the quantification of the dialysis dose, two parameters are most commonly used, namely the K_t/V value (normalised dose of dialysis) and the urea reduction rate, yet the prescribed dialysis dose often differs from the actual delivered dialysis dose. Currently, no interactive process is available to ensure optimal treatment. The aim of this study was to investigate the potential for an “electronic nose” as a novel monitoring tool for haemodialysis. Blood samples were analysed using an electronic nose, comprising an array of 14 conducting polymer sensors, and compared to traditional biochemistry. Principal component analysis and hierarchical cluster analysis were applied to evaluate the data, and demonstrated the ability to distinguish between pre-dialysis blood from post-dialysis blood independent of the method used. It is concluded that the electronic nose is capable of discriminating pre-dialysis from post-dialysis blood and hence, together with an appropriate classification model, suitable for on-line monitoring.     

Bio-Benchmarking of Electronic Nose Sensors

Background

Electronic noses, E-Noses, are instruments designed to reproduce the performance of animal noses or antennae but generally they cannot match the discriminating power of the biological original and have, therefore, been of limited utility. The manner in which odorant space is sampled is a critical factor in the performance of all noses but so far it has been described in detail only for the fly antenna.

Methodology

Here we describe how a set of metal oxide (MOx) E-Nose sensors, which is the most commonly used type, samples odorant space and compare it with what is known about fly odorant receptors (ORs).

Principal Findings

Compared with a fly''s odorant receptors, MOx sensors from an electronic nose are on average more narrowly tuned but much more highly correlated with each other. A set of insect ORs can therefore sample broader regions of odorant space independently and redundantly than an equivalent number of MOx sensors. The comparison also highlights some important questions about the molecular nature of fly ORs.

Conclusions

The comparative approach generates practical learnings that may be taken up by solid-state physicists or engineers in designing new solid-state electronic nose sensors. It also potentially deepens our understanding of the performance of the biological system.     

NEURAL METHODS OF CALIBRATION OF SENSORS FOR GAS MEASUREMENTS AND AROMA IDENTIFICATION SYSTEM

The article presents the neural methods of calibration of gas sensors for use in an artificial electronic nose for gas measurements. Different neural network solutions will be presented and compared. They include the classical multilayer perceptron, neuro-fuzzy networks and support vector machines. The other aspect illustrated in the article is the introductory preprocessing of the measured sensor signals in order to attain the highest possible efficiency of the gas measuring system. The theoretical considerations will be supported by the numerical experiments concerning the application of the electronic nose. The first practical aspect is concerned with the application of the developed system for classification problems and will be illustrated in the examples of the recognition of the biocomponents in the gasoline and the recognition of smells of cosmetic cream at the aging process. The second one belongs to the estimation problem and is concerned with the determination of the concentration of the particular gas components in the mixture of gases.

PRACTICAL APPLICATIONS

The results presented in the article may find practical application for calibration of the electronic nose in gas measurements. The electronic nose is widely used for smell recognition. It may find practical application in the petroleum, cosmetics or food industry for the assessment of the quality of their products. Military application is also of great interest.     

The bioelectronic nose and tongue using olfactory and taste receptors: Analytical tools for food quality and safety assessment

Food intake is the primary method for obtaining energy and component materials in the human being. Humans evaluate the quality of food by combining various facets of information, such as an item of food's appearance, smell, taste, and texture in the mouth. Recently, bioelectronic noses and tongues have been reported that use human olfactory and taste receptors as primary recognition elements, and nanoelectronics as secondary signal transducers. Bioelectronic sensors that mimic human olfaction and gustation have sensitively and selectively detected odor and taste molecules from various food samples, and have been applied to food quality assessment. The portable and multiplexed bioelectronic nose and tongue are expected to be used as next-generation analytical tools for rapid on-site monitoring of food quality. In this review, we summarize recent progress in the bioelectronic nose and tongue using olfactory and taste receptors, and discuss the potential applications and future perspectives in the food industry.     

Physiologically Motivated Monitoring of Fermentation Processes by Means of an Electronic Nose

An on‐line approach of non‐invasive monitoring of the physiological changes in fermentation processes is presented. In yeast batch and bacterial fed‐batch fermentations it is shown that metabolic state changes can be revealed using an electronic nose. The transient responses of the gas sensors to the changes in the composition of the volatiles emitted from the cell cultures during fermentation are used to retrieve a semi‐quantitative representation of the physiological state of the cultures. With the sensor responses of the electronic nose it is shown that physiological variables such as rates of growth, substrate uptake and product formation can be depicted. The non‐invasive method thus seems as a pertinent alternative to conventional bioreactor monitoring methods.     

Analysis of Medication Off-odors Using an Electronic Nose

Packaging materials have been implicated as a source for off-odorsin pharmaceutical products. A new instrumentation method employingan array of conducting polymer gas sensors was used to identifythe offending packaging components in the canister of a pharmaceuticalinhalant. A case study is described in which tainted inhalersas well as elastomeric components of the canisters were ‘sniffed’by the electronic nose. The electronic nose was able to differentiatebetween tainted and untainted canisters. Signal processing algorithmsperformed on the raw data from the sensors suggested that specificelastomeric components were responsible for the off-odor. Afurther experiment suggested that the propellant (Freon) extractedthe odor from the elastomeric components as the medication wasexpelled from the canister. These data indicate that the electronicnose is a potential tool to solve odor problems in which humanodor assessment is not feasible due to excess exposure to themedically active ingredient. Chem. Senses 22: 119–128,1997.     

Predicting sporulation events in a bioreactor using an electronic nose

An electronic nose (EN) based on a non- specific multi-sensor array was used to accurately estimate sporulation events and the spore concentration of Bacillus subtilis cultures. The array included 6 metal oxide sensors (MOS), 10 metal oxide semiconductor field effect transistors (MOSFET), one CO(2) infrared sensor and one humidity sensor. The EN was used to monitor the gas emissions from B. subtilis bioreactions during both batch and fed-batch operation. The signal pattern produced by the sensors was evaluated by principal component analysis (PCA) and training cultivations were used to build a model. The arc length of the PCA trajectories was successfully correlated to the off-line spore count; a strong linear correlation (R(2) = 0.992) between the numerical integration of the curves and the measured spore concentration was established. The fast responses of the sensors in combination with the robust correlation with the off-line determination of spore concentration establish this EN device as a convenient tool for monitoring sporulation events in bioprocesses.     

Diagnosis of acute puerperal metritis by electronic nose device analysis of vaginal discharge in dairy cows

The objective of this study was to estimate the diagnostic accuracy of an electronic nose device using vaginal discharge samples to diagnose acute puerperal metritis (APM) in dairy cows. Uterine fluid was sampled manually with a gloved hand and under sterile conditions for electronic nose device analysis (day in milk (DIM) 2, 5, and 10) and bacteriologic examination (DIM 5), respectively, and on additional days, if APM was diagnosed during the daily clinical examinations. A dataset containing samples from 70 cows was used to create a model and to validate the APM status predicted by this model, respectively. Half of the dataset (n = 35; 14 healthy and 21 metritic cows) was provided with information regarding the APM diagnosis and contained all three measurements (DIM 2, 5, and 10) for each cow and was used as a training set whereas the second half was blinded (n = 35; 14 healthy and 21 metritic cows) and contained only the samples collected on DIM 5 of each cow and was used to validate the created prediction model. A receiver operating characteristic curve was calculated using the prediction results of the validation test. The best observed sensitivity was 100% with specificity of 91.6% when using a threshold value of 0.3. The calculated P-value for the receiver operating characteristic curve was less than 0.01. Overall, Escherichia coli was isolated in eight of 28 (28.6%) and 22 of 42 (52.4%) samples collected from healthy and metritic cows, respectively. Trueperella pyogenes and Fusobacterium necrophorum were isolated in 14 and six of 28 (50.0% and 21.4%) and 17 and 16 of 42 (40.5% and 38.1%) samples collected from healthy and metritic cows, respectively. The prevalence of Escherichia coli and Trueperella pyogenes was similar in the samples obtained from metritic cows used for the training set and the validation test. The results are promising especially because of the objective nature of the measurements obtained by the electronic nose device.     

Exhaled Breath Analysis Using Electronic Nose in Cystic Fibrosis and Primary Ciliary Dyskinesia Patients with Chronic Pulmonary Infections

The current diagnostic work-up and monitoring of pulmonary infections may be perceived as invasive, is time consuming and expensive. In this explorative study, we investigated whether or not a non-invasive exhaled breath analysis using an electronic nose would discriminate between cystic fibrosis (CF) and primary ciliary dyskinesia (PCD) with or without various well characterized chronic pulmonary infections. We recruited 64 patients with CF and 21 with PCD based on known chronic infection status. 21 healthy volunteers served as controls. An electronic nose was employed to analyze exhaled breath samples. Principal component reduction and discriminant analysis were used to construct internally cross-validated receiver operator characteristic (ROC) curves. Breath profiles of CF and PCD patients differed significantly from healthy controls p = 0.001 and p = 0.005, respectively. Profiles of CF patients having a chronic P. aeruginosa infection differed significantly from to non-chronically infected CF patients p = 0.044. We confirmed the previously established discriminative power of exhaled breath analysis in separation between healthy subjects and patients with CF or PCD. Furthermore, this method significantly discriminates CF patients suffering from a chronic pulmonary P. aeruginosa (PA) infection from CF patients without a chronic pulmonary infection. Further studies are needed for verification and to investigate the role of electronic nose technology in the very early diagnostic workup of pulmonary infections before the establishment of a chronic infection.     

电子鼻技术在快速检测小麦矮腥黑穗病菌中的应用

由小麦矮腥黑穗病菌(TCK)引起的小麦矮腥黑穗病是我国重要的检疫性病害,为明确电子鼻技术在快速检测小麦矮腥黑穗病菌方面的可行性,利用电子鼻对含有TCK和小麦光腥黑穗病菌(TFL)不同冬孢子数(50g小麦种子中冬孢子数分别为0、100、101、102、103、104、105)的小麦进行了检测,采用主成分分析法(PCA)和线性判别法(LDA)进行数据分析。结果发现,这2种分析方法均可将不含TCK冬孢子的小麦和含TCK冬孢子的小麦区分开来,而且通过LDA分析,可将TCK冬孢子含量为100、101、102及103以上的处理区分开来。另外,通过PCA分析,可将TCK与TFL区分开来。此结果为电子鼻技术在快速检测小麦矮腥黑穗病菌中的应用奠定了基础。     

Monitoring the aroma production during wine-must fermentation with an electronic nose.

This work discusses the feasibility of using the electronic nose for the on-line and real-time monitoring of the production of a complex aroma profile during a bioconversion process. As a case study, the formation of the muscatel aroma during the wine-must fermentation was selected. During wine-must fermentation, aroma compounds responsible for the organoleptic character are produced in the ppm range, while simultaneously one of the main metabolic products, ethanol, is produced in much higher quantities (up to 10% wt). Because the sensors of the electronic nose array are cross-selective to different volatile compounds, it was investigated in detail how far the electronic nose was able to evaluate the aroma profile along the fermentation. This article discusses and evaluates subsequently the integration of a membrane separation process-organophilic pervaporation-for selectively enriching aroma compounds relative to ethanol, to improve sample discrimination.     

A bio-inspired two-layer multiple-walled carbon nanotube-polymer composite sensor array and a bio-inspired fast-adaptive readout circuit for a portable electronic nose

We report a fully integrated, portable, battery-operated electronic nose system comprising a bio-inspired two-layer multiple-walled carbon nanotube (MWNT)-polymer composite sensor array, a bio-inspired fast-adaptive readout circuit, and a microprocessor embedded with a pattern recognition algorithm. The two-layer MWNT-polymer composite sensor is simple to operate, and the membrane quality can be easily controlled. These two-layer membranes have improved sensitivity and stability. The fast-adaptive readout circuit responds to the sensor response, while tuning out the long-term constant background humidity, temperature, and odors. This portable electronic nose system successfully classified four complex alcohol samples 40 times for each sample; these samples were sake, sorghum liquor, medical liquor, and whisky.     

Potential for detection of microorganisms and heavy metals in potable water using electronic nose technology

Studies have been carried out to determine the potential for the detection of different microbial species (Enterobacter aerogenes, Escherichia coli, Pseudomonas aeruginosa), alone and in the presence of low concentrations of different heavy metals (As, Cd, Pb and Zn) in bottled, reverse osmosis (RO) and tap water, using an electronic nose. Studies show that it is possible to discriminate control water samples from water contaminated with 0.5 ppm of a mixture of metals. The presence of heavy metals may modify the activity of microorganisms and thus the volatile production patterns. Bacterial species at 10(2)-10(4) colony forming units (CFUs) ml(-1) could be detected after 24 h of incubation. Work is in progress to identify the limits of detection for a range of other microorganisms, including, fungi and cyanobacteria, and chlorinated phenols using electronic nose technology.     

Estimation of bacteriological spoilage of pork cutlets by electronic nose

The utility of chemosensor array (EN) signals of head-space volatiles of aerobically stored pork cutlets as a non-invasive technique for monitoring their microbiological load was studied during storage at 4, 8 and 12 degrees C, respectively. The bacteriological quality of the meat samples was determined by standard total aerobic plate counts (TAPC) and colony count of selectively estimated Pseudomonas (PS) spp., the predominant aerobic spoilage bacteria. Statistical analysis of the electronic nose measurements were principal component analysis (PCA), and canonical discriminant analysis (CDA). Partial least squares (PLS) regression was used to model correlation between microbial loads and EN signal responses, the degree of bacteriological spoilage, independently of the temperature of the refrigerated storage. Sensor selection techniques were applied to reduce the dimensionality and more robust calibration models were computed by determining few individual sensors having the smallest cross correlations and highest correlations with the reference data. Correlations between the predicted and "real" values were given on cross-validated data from both data reduced models and for full calibrations using the 23 sensor elements. At the same time, sensorial quality of the raw cutlets was noted subjectively on faultiness of the odour and colour, and drip formation of the samples. These preliminary studies indicated that the electronic nose technique has a potential to detect bacteriological spoilage earlier or at the same time as olfactory quality deterioration.