A real-world assessment of stage I lung cancer through electronic nose technology

INTRODUCTION

Electronic nose (E-nose) technology has demonstrated excellent sensitivity and specificity in the setting of lung cancer screening. However, the performance of E-nose specifically for early-stage tumors remains unclear. Therefore, the aim of our study was to assess the diagnostic performance of E-nose technology in clinical stage I lung cancer.

METHODS

This Phase-IIc trial (NCT04734145) included patients diagnosed with a single ≥50% solid stage I nodule. Exhalates were prospectively collected from January 2020 to August 2023. Blinded bioengineers analyzed the exhalates, using E-nose technology to determine the probability of malignancy. Patients were stratified into 3 risk groups (low-risk, <0.2; moderate-risk, ≥0.2 to 0.7; high-risk, ≥0.7). The primary outcome was the diagnostic performance of E-nose versus histopathology (accuracy and F1 score). The secondary outcome was the clinical performance of the E-nose versus clinicoradiological prediction models.

RESULTS

Based on the predefined cut-off (<0.20), E-nose agreed with histopathological results in 86% of cases, achieving an F1 score of 92.5%, based on 86 true positives, 2 false negatives, and 12 false positives (n=100). Compared with Swensen and Brock models, E-nose would refer fewer patients with malignant nodules to observation (Low-risk: 2 vs. 9 and 11; respectively; p=0.028 and p=0.011) and more patients with malignant nodules to treatment without biopsy (High-risk: 27 vs. 19 and 6; respectively; p=0.057 and p<0.001).

CONCLUSIONS

In the setting of clinical stage I lung cancer, E-nose has good agreement with histopathology. Accordingly, E-nose technology can be used in addition to imaging or as part of a "multiomics" platform.

Use of Sensor Array Analysis to Detect Ovarian Cancer through Breath, Urine, and Blood: A Case-Control Study

Ovarian cancer (OC) is the eighth most common cancer in women. Since screening programs do not exist, it is often diagnosed in advanced stages. Today, the detection of OC is based on clinical examination, transvaginal ultrasound (US), and serum biomarker (Carbohydrate Antigen 125 (CA 125) and Human Epididymis Protein 4 (HE4)) dosage, with a sensitivity of 88% and 95%, respectively, and a specificity of 84% for US and 76% for biomarkers. These methods are clearly not enough, and OC in its early stages is often missed. Many scientists have recently focused their attention on volatile organic compounds (VOCs). These are gaseous molecules, found in the breath, that could provide interesting information on several diseases, including solid tumors. To detect VOCs, an electronic nose was invented by a group of researchers. A similar device, the e-tongue, was later created to detect specific molecules in liquids. For the first time in the literature, we investigated the potential use of the electronic nose and the electronic tongue to detect ovarian cancer not just from breath but also from urine, blood, and plasma samples.

Development of a Universal Validation Protocol and an Open-Source Database for Multi-Contextual Facial Expression Recognition

Facial expression recognition (FER) poses a complex challenge due to diverse factors such as facial morphology variations, lighting conditions, and cultural nuances in emotion representation. To address these hurdles, specific FER algorithms leverage advanced data analysis for inferring emotional states from facial expressions. In this study, we introduce a universal validation methodology assessing any FER algorithm's performance through a web application where subjects respond to emotive images. We present the labelled data database, FeelPix, generated from facial landmark coordinates during FER algorithm validation. FeelPix is available to train and test generic FER algorithms, accurately identifying users' facial expressions. A testing algorithm classifies emotions based on FeelPix data, ensuring its reliability. Designed as a computationally lightweight solution, it finds applications in online systems. Our contribution improves facial expression recognition, enabling the identification and interpretation of emotions associated with facial expressions, offering profound insights into individuals' emotional reactions. This contribution has implications for healthcare, security, human-computer interaction, and entertainment.

Detecting Dementia by Saliva Analysis: A Fingerprinting Unobtrusive Method Based on a Fast and Cheap Sensor System

BACKGROUND

Recent studies have shown that oxidative stress plays a relevant role in Alzheimer's disease (AD), and in the pathogenesis of vascular dementia (VaD). New diagnostic methods look for biological samples with non-invasive sampling methods. Among these, saliva shows an increase in oxidative stress products, thus a corresponding reduction in antioxidant products were found in dementia cases compared to healthy controls. Compounds identified in saliva include some hydrocarbons whose production has been related to the presence of reactive oxygen species.

OBJECTIVE

The hypothesis is that the voltammetric analysis performed on saliva could be a useful test for diagnosing dementia, potentially discriminating between AD and VaD.

METHODS

A single-center observational study was conducted on patients referred to the dementia clinic in the Neurology area and healthy controls recruited in the Orthopedics area of the Campus Bio-Medico Hospital in Rome. The study was aimed at evaluating the discriminative properties of salivary voltammetric analysis between healthy subjects and patients with dementia and, as a secondary outcome, between AD and VaD. A total of 69 subjects were enrolled, including 29 healthy controls, 20 patients with AD, and 20 patients with VaD. The degree of cognitive impairment was classified on the basis of the Mini-Mental State Examination score.

RESULTS

The results obtained are promising, with an accuracy of 79.7%, a sensitivity of 82.5%, and a specificity of 75.8%, in the discrimination of dementia versus controls.

CONCLUSIONS

The methods tested demonstrate to be relevant in the discrimination between dementia and controls. A confirmatory study is already running.

Micromachined Tools Using Acoustic Wave Triggering for the Interaction with the Growth of Plant Biological Systems

A plant biological system is exposed to external influences. In general, each plant has its characteristics and needs with specific interaction mechanisms adapted to its survival. Interactions between systems can be examined and modeled as energy exchanges of mechanical, chemical or electrical variables. Thus, each specific interaction can be examined by triggering the system via a specific stimulus. The objective of this work was to study a specific stimulus (mechanical stimulation) as a driver of plants and their interaction with the environment. In particular, the experimental design concerns the setting up and testing of an automatic source of mechanical stimuli at different wavelengths, generated by an electromechanical transducer, to induce a micro-interaction in plants (or in parts of them) that produces a specific behavior (hypothesis) of plants. Four different experimental setups were developed for this work, each pursuing the same objective: the analysis of the germination process induced by stimulation by sound waves in the audible range. It can be said that the introduction of sound waves as a stimulant or a brake for the growth of plants can offer significant advantages when used on a large scale in the primary sector, since these effects can be used instead of polluting chemical solutions.

Microsystem Nodes for Soil Monitoring via an Energy Mapping Network: A Proof-of-Concept Preliminary Study

The need for accurate information and the availability of novel tool and technological advances in agriculture have given rise to innovative autonomous systems. The aim is to monitor key parameters for optimal water and fertilizer management. A key issue in precision agriculture is the in situ monitoring of soil macronutrients. Here, a proof-of-concept study was conducted that tested two types of sensors capable of capturing both the electrochemical response of the soil and the electrical potential generated by the interaction between the soil and plants. These two sensors can be used to monitor large areas using a network approach, due to their small size and low power consumption. The voltammetric sensor (BIONOTE-L) proved to be able to characterize different soil samples. It was able, indeed, to provide a reproducible voltammetric fingerprint specific for each soil type, and to monitor the concentration of CaCl₂ and NaCl in the soil. BIONOTE-L can be coupled to a device capable of capturing the energy produced by interactions between plants and soil. As a consequence, the functionality of the microsystem node when applied in a large-area monitoring network can be extended. Additional calibrations will be performed to fully characterize the instrument node, to implement the network, and to specialize it for a particular application in the field.

Gut Microbiota and Related Electronic Multisensorial System Changes in Subjects With Symptomatic Uncomplicated Diverticular Disease Undergoing Rifaximin Therapy

Background: Intestinal dysbiosis might play a pathogenetic role in subjects with symptomatic uncomplicated diverticular disease (SUDD), but the effect of rifaximin therapy has been scantly explored with regard to gut microbiota variations in patients with SUDD. Aims: To verify to which extent rifaximin treatment affects the gut microbiota and whether an electronic multisensorial assessment of stools and breath has the potential for detecting these changes. Methods: Breath and stool samples were collected from consecutive patients with SUDD before and after a 7 days' therapy with rifaximin. Stool microbiota was assessed, and the electronic multisensorial assessment was carried out by means of the BIONOTE electronic (e-)tongue in stools and (e-)nose in breath. Results: Forty-three subjects (female 60%, median age 66 years) were included, and 20 (47%) reported clinical improvement after rifaximin therapy. Alpha and beta diversity of stool microbiota did not significantly change after treatment, while a significant variation of selected taxa was shown (i.e., Citrobacter, Coprococcus, Anaerotruncus, Blautia, Eggerthella lenta, Dehalobacterium, SMB53, and Haemophilus parainfluenzae). Overall, the electronic multisensorial system suboptimally mirrored microbiota changes, but it was able to efficiently predict patients' clinical improvement after rifaximin with accuracies ranging from 0.81 to 0.98. Conclusions: In patients with SUDD, rifaximin administration is associated with significant variation of selected taxa. While inaccurate in predicting gut microbiota change, an electronic multisensorial system, made up of e-tongue and e-nose, was able to predict clinical improvement, thus potentially qualifying as an easy and cheap tool to forecast subjects taking most likely benefit from rifaximin therapy.

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.

Development and Test of a Portable ECG Device with Dry Capacitive Electrodes and Driven Right Leg Circuit

The use of wearable sensors for health monitoring is rapidly growing. Over the past decade, wearable technology has gained much attention from the tech industry for commercial reasons and the interest of researchers and clinicians for reasons related to its potential benefit on patients' health. Wearable devices use advanced and specialized sensors able to monitor not only activity parameters, such as heart rate or step count, but also physiological parameters, such as heart electrical activity or blood pressure. Electrocardiogram (ECG) monitoring is becoming one of the most attractive health-related features of modern smartwatches, and, because cardiovascular disease (CVD) is one of the leading causes of death globally, the use of a smartwatch to monitor patients could greatly impact the disease outcomes on health care systems. Commercial wearable devices are able to record just single-lead ECG using a couple of metallic contact dry electrodes. This kind of measurement can be used only for arrhythmia diagnosis. For the diagnosis of other cardiac disorders, additional ECG leads are required. In this study, we characterized an electronic interface to be used with multiple contactless capacitive electrodes in order to develop a wearable ECG device able to perform several lead measurements. We verified the ability of the electronic interface to amplify differential biopotentials and to reject common-mode signals produced by electromagnetic interference (EMI). We developed a portable device based on the studied electronic interface that represents a prototype system for further developments. We evaluated the performances of the developed device. The signal-to-noise ratio of the output signal is favorable, and all the features needed for a clinical evaluation (P waves, QRS complexes and T waves) are clearly readable.

BIONOTE as an Innovative Biosensor for Measuring Endocannabinoid Levels

In this study, a novel approach was developed to quantify endocannabinoids (eCBs), and was based on the liquid biosensor BIONOTE. This device is composed of a probe that can be immersed in a solution, and an electronic interface that can record a current related to the oxy-reductive reactions occurring in the sample. The two most representative members of eCBs have been analysed in vitro by BIONOTE: anandamide (N-arachidonoylethanolamine, AEA) and 2-arachidonoylglycerol (2-AG). Bovine serum albumin was used to functionalize the probe and improve the sensibility of the whole analytical system. We show that BIONOTE is able to detect both AEA and 2-AG at concentrations in the low nanomolar range, and to discriminate between these eCBs and their moieties arachidonic acid, ethanolamine and glycerol. Notably, BIONOTE distinguished these five different molecules, and it was also able to quantify AEA in human plasma. Although this is just a proof-of-concept study, we suggest BIONOTE as a cheap and user-friendly prototype sensor for high throughput quantitation of eCB content in biological matrices, with an apparent diagnostic potential for tomorrow’s medicine.

CO2 and O2 Detection by Electric Field Sensors

In this work an array of chemical sensors for gas detection has been developed, starting with a commercial sensor platform developed by Microchip (GestIC), which is normally used to detect, trace, and classify hand movements in space. The system is based on electric field changes, and in this work, it has been used as mechanism revealing the adsorption of chemical species CO2 and O2. The system is composed of five electrodes, and their responses were obtained by interfacing the sensors with an acquisition board based on an ATMEGA 328 microprocessor (Atmel MEGA AVR microcontroller). A dedicated measurement chamber was designed and prototyped in acrylonitrile butadiene styrene (ABS) using an Ultimaker3 3D printer. The measurement cell size is 120 × 85 mm. Anthocyanins (red rose) were used as a sensing material in order to functionalize the sensor surface. The sensor was calibrated using different concentrations of oxygen and carbon dioxide, ranging from 5% to 25%, mixed with water vapor in the range from 50% to 90%. The sensor exhibits good repeatability for CO2 concentrations. To better understand the sensor response characteristics, sensitivity and resolution were calculated from the response curves at different working points. The sensitivity is in the order of magnitude of tens to hundreds of µV/% for CO2, and of µV/% in the case of O2. The resolution is in the range of 10-1%-10-3% for CO2, and it is around 10-1% for O2. The system could be specialized for different fields, for environmental, medical, and food applications.

A Sensor Platform for Athletes' Training Supervision: A Proof of Concept Study

One of the basic needs of professional athletes is the real-time and non-invasive monitoring of their activities. The use of these kind of data is necessary to develop strategies for specific tailored training in order to improve performances. The sensor system presented in this work has the aim to adopt a novel approach for the monitoring of physiological parameters, and athletes' performances, during their training. The anaerobic threshold is herein identified with the monitoring of the lactate concentration and the respiratory parameters. The data collected by the sensor are used to build a model using a supervised method (based on the partial least squares method, PLS) to predict the values of the parameters of interest. The sensor is able to measure the lactate concentration from a sample of saliva and it can estimate a respiratory parameter, such as maximal oxygen consumption, maximal carbon dioxide production and respiratory rate from a sample of exhaled breath. The main advantages of the device are the low power; the wireless communication; and the non-invasive sampling method, which allow its use in a real context of sport practice.

Use of voltammetric analysis for fast and objective discrimination of the etiology, evolution, and bacterial infection of lower limb ulcers

The timely recognition of leg ulcers (LU) etiology and infection is pivotal to optimize management and accelerate healing. The objective of this proof-of-concept study was to test the diagnostic performance of voltammetric analysis (VA) on ulcer exudate to identify LU etiology, infection, and predict clinical course. We enrolled 25 patients aged ≥60 years, affected by 42 venous/arterial LU. Clinical examination (Leg Ulcer Measurement Tool score, LUMT), swab culture, and VA were performed at baseline and 30 days. The ability of VA to predict outcomes was tested using partial least square-discrimination analysis. Mean age was 75 years (SD 11.1), 9/25 were male. The accuracy, sensitivity, and specificity vs. etiology were 97.4, 100%, and 94.1%, respectively; the corresponding figures were 95.2%, 100%, 88.9%, for infection and 94%, 84.6%, 100% for predicted objective LUMT worsening. VA is a promising diagnostic/prognostic tool for management of LU that may allow a more timely targeted therapy.

Identification and prospective stability of electronic nose (eNose)-derived inflammatory phenotypes in patients with severe asthma

BACKGROUND

Severe asthma is a heterogeneous condition, as shown by independent cluster analyses based on demographic, clinical, and inflammatory characteristics. A next step is to identify molecularly driven phenotypes using "omics" technologies. Molecular fingerprints of exhaled breath are associated with inflammation and can qualify as noninvasive assessment of severe asthma phenotypes.

OBJECTIVES

We aimed (1) to identify severe asthma phenotypes using exhaled metabolomic fingerprints obtained from a composite of electronic noses (eNoses) and (2) to assess the stability of eNose-derived phenotypes in relation to within-patient clinical and inflammatory changes.

METHODS

In this longitudinal multicenter study exhaled breath samples were taken from an unselected subset of adults with severe asthma from the U-BIOPRED cohort. Exhaled metabolites were analyzed centrally by using an assembly of eNoses. Unsupervised Ward clustering enhanced by similarity profile analysis together with K-means clustering was performed. For internal validation, partitioning around medoids and topological data analysis were applied. Samples at 12 to 18 months of prospective follow-up were used to assess longitudinal within-patient stability.

RESULTS

Data were available for 78 subjects (age, 55 years [interquartile range, 45-64 years]; 41% male). Three eNose-driven clusters (n = 26/33/19) were revealed, showing differences in circulating eosinophil (P = .045) and neutrophil (P = .017) percentages and ratios of patients using oral corticosteroids (P = .035). Longitudinal within-patient cluster stability was associated with changes in sputum eosinophil percentages (P = .045).

CONCLUSIONS

We have identified and followed up exhaled molecular phenotypes of severe asthma, which were associated with changing inflammatory profile and oral steroid use. This suggests that breath analysis can contribute to the management of severe asthma.

Methodological considerations for large-scale breath analysis studies: lessons from the U-BIOPRED severe asthma project

Methods for breath sampling and analysis require robust quality assessment to minimise the risk of false discoveries. Planning large-scale multi-site breath metabolite profiling studies also requires careful consideration of systematic and random variation as a result of sampling and analysis techniques. In this study we use breath sample data from the recent U-BIOPRED cohort to evaluate and discuss some important methodological considerations such as batch variation and correction, variation between sites, storage and transportation, as well as inter-instrument analytical differences. Based on this we provide a summary of recommended best practices for new large scale multi-site studies.

Advances in the Electronics for Cyclic Voltammetry: the Case of Gas Detection by Using Microfabricated Electrodes

This paper presents an advanced voltammetric system to be used as electronic tongue for liquid and gas analysis. It has been designed to be more flexible and accurate with respect to other existing and similar systems. It features improved electronics and additional operative conditions. Among others these include the possibility to optically excite the solution and to treat the output signal by a differentiation process in order to better evidence the existence of small details in the response curve. Finally by the same type of tongue preliminary results are shown dealing with O₂ and CO₂ concentration measurements in appropriate solutions.

Chemically mediated species recognition in two sympatric Grayling butterflies: Hipparchia fagi and Hipparchia hermione (Lepidoptera: Nymphalidae, Satyrinae)

Pheromones are known to play an important role in butterfly courtship and may influence both individual reproductive success and reproductive isolation between species. Recent studies have focused on courtship in Hipparchia butterflies (Nymphalidae: Satyrinae) emphasizing morphological and behavioural traits, as well as genetic differences. Behavioural observations suggested a role for chemical cues in mate and species recognition, where the androconial scales on the forewings of these species may be involved in chemical communication between individuals. Cchemical-mediated signals have received relatively little attention in this genus. Here, we report the results of a three-year investigation of the volatile organic compounds (VOCs) released by Hipparchia fagi and H. hermione in order to identify differences in VOCs between these species where they live in syntopy. Our study was carried out using an array of cross-selective sensors known as an "Electronic Nose" (EN) that operates by converting chemical patterns into patterns of sensor signals. While the identity of volatile compounds remained unknown, sensor signals can be compared to identify similar or dissimilar chemical patterns. Based on the EN signals, our results showed that: 1) the two sexes have a similar VOCs pattern in H. fagi, while they significantly diverge in H. hermione; 2) VOCs patterns were different between females of the two species, while those of males were not.

Cluster analysis on breath print of newly diagnosed COPD patients: effects of therapy

BACKGROUND

Chronic obstructive pulmonary disease (COPD) is a highly heterogeneous disease and airflow limitation and symptoms only partially capture such heterogeneity. Since COPD is known to affect the production of volatile organic compounds (VOCs), we aimed to verify to which extent exhaled VOCs can characterize newly diagnosed COPD patients and changes in response to inhaled therapy.

MATERIALS AND METHODS

Fifty newly diagnosed COPD patients were consecutively recruited among those attending the pulmonary medicine outpatient clinic at 'Campus Bio-Medico' University Hospital. VOCs were collected using the Pneumopipe^® and analysed by the BIONOTE electronic nose both at baseline and after 12 weeks of inhaled therapy. Patients were grouped using K-mean cluster analysis on BIONOTE responses and the obtained clusters were compared via non-parametric tests.

RESULTS

We identified three clusters of subjects: (a) without remarkable comorbidities; (b) with air trapping and higher BODE index score (mean 1.2); (c) without air trapping and with a lower BODE index. Inhaled bronchodilators caused a quantitative reduction in the amound of VOCs, while inhaled steroids provided a qualitative modification of the breath profile.

CONCLUSION

VOCs patterns categorize newly diagnosed COPD subjects. VOCs production declines after bronchodilators administration and changes in quality after topic steroid treatment.

Validation of exhaled volatile organic compounds analysis using electronic nose as index of COPD severity

Aim

Six-minute walking test distance (6MWD) and body mass index, obstruction, dyspnea and exercise (BODE) index are measures of functional status in COPD patients, but require space, time and patient's compliance. Exhaled volatile organic compounds (VOCs) analysis via electronic nose is a quick and easy method that has already been used to discriminate COPD phenotypes. The aim of this study is to evaluate whether VOCs analysis can predict functional status and its variation over time in COPD patients.

Methods

A monocentric prospective study with 1 year of follow-up was carried out. All patients underwent pulmonary function tests, arterial gas analysis, bioimpedance analysis, 6-minute walking test, and VOCs collection. Exhaled breath was collected with Pneumopipe^® and analyzed using BIONOTE electronic nose. Outcomes prediction was performed by k-fold cross-validated partial least square discriminant analysis: accuracy, sensitivity and specificity as well as Cohen's kappa for agreement were calculated.

Results

We enrolled 63 patients, 60.3% men, with a mean age of 71 (SD: 8) years, median BODE index of 1 (interquartile range: 0-3) and mean 6MWD normalized by squared height (n6MWD) of 133.5 (SD: 42) m/m². The BIONOTE predicted baseline BODE score (dichotomized as BODE score <3 or ≥3) with an accuracy of 86% and quartiles of n6MWD with an accuracy of 79%. n6MWD decline more than the median value after 1 year was predicted with an accuracy of 86% by BIONOTE, 52% by Global Initiative for Chronic Obstructive Lung Disease (GOLD) class and 78% by combined BIONOTE and GOLD class.

Conclusion

Exhaled VOCs analysis identifies classes of BODE and n6MWD quartiles, and outperforms GOLD classification in predicting n6MWD variation.

Analysis of volatile organic compounds: an innovative approach to heart failure characterization in older patients

BACKGROUND

Analysis of exhaled volatile organic compounds (VOCs) may be applied for diagnostic purposes in some chronic diseases, but there are no data on their role for discriminating people with congestive heart failure (CHF), particularly in older patients where natriuretic peptides have lower accuracy. We evaluated whether VOCs analysis can discriminate patients with or without CHF, stratify CHF severity and predict the response to therapy of decompensated CHF.

METHODS AND RESULTS

We recruited 89 subjects admitted to an acute care ward with acutely decompensated CHF, 117 healthy controls and 103 chronic obstructive pulmonary disease (COPD) controls. CHF patients performed echocardiography. VOCs were collected using the Pneumopipe^® and analyzed with the BIONOTE electronic nose. Partial least square analysis was used to evaluate the discriminative capacity of VOCs. Accuracy in discrimination of CHF versus healthy and COPD controls was 81% and 69%, respectively; accuracy did not decrease in a sensitivity analysis excluding subjects younger than 65 and older than 80 years. In CHF patients VOCs pattern could predict with fair precision ejection fraction and systolic pulmonary arterial pressure, but not changes in weight due to therapy.

CONCLUSIONS

VOCs pattern is able to discriminate older CHF patients from healthy people and COPD patients and correlates with cardiac function markers.

Voltammetric analysis for fast and inexpensive diagnosis of urinary tract infection: a diagnostic study

BACKGROUND

Dipstick test is widely used to support the diagnosis of urinary tract infections (UTI). It is effective in ruling out UTI, but urine culture is needed for diagnosis confirmation. In this study we compared the accuracy of voltammetric analysis (VA) with that of DT to detect UTI (diagnosed using urine culture), and its usefulness as a second-stage test in people with positive DT.

METHODS

142 patients were enrolled with no exclusion criteria. VA was performed using the BIONOTE device. Partial Least Square Discrimination Analysis was used to predict UTI based on VA data; diagnostic performance was evaluated using sensitivity, specificity, positive and negative predictive values (PPV and NPV, respectively), positive and negative likelihood ratios (LR), accuracy, diagnostic odds ratio (DOR).

RESULTS

Mean age was 76.6 years (SD 12.6), 57% were male. VA had a better overall performance respect to DT in detecting UTI with accuracy 81.7% vs 75.9%, specificity 90.8% vs 82.5%, PPV 75% vs 61.4%, positive LR 6.68 vs 3.5, DOR 17.7 vs 7.47; sensibility, NPV and negative LR of the two tests were similar. VA had an accuracy of 82.4% in discriminating bacterial from fungal infections. When added as a second-stage test, VA identified 9 of the 17 false positive patients, with a net specificity of 91.7%, sensitivity 54%, PPV 75% and NPV 81%.

CONCLUSIONS

VA is a quick and easy method that may be used as a second stage after DT to reduce the number of urine culture and of inappropriate antibiotic prescriptions.

An Electronic System for the Contactless Reading of ECG Signals

The aim of this work is the development of a contactless capacitive sensory system for the detection of (Electrocardiographic) ECG-like signals. The acquisition approach is based on a capacitive coupling with the patient body performed by electrodes integrated in a front-end circuit. The proposed system is able to detect changes in the electric charge related to the heart activity. Due to the target signal weakness and to the presence of other undesired signals, suitable amplification stages and analogue filters are required. Simulated results allowed us to evaluate the effectiveness of the approach, whereas experimental measurements, recorded without contact to the skin, have validated the practical effectiveness of the proposed architecture. The system operates with a supply voltage of ±9 V with an overall power consumption of about 10 mW. The analogue output of the electronic interface is connected to an ATmega328 microcontroller implementing the A/D conversion and the data acquisition. The collected data can be displayed on any multimedia support for real-time tracking applications.

Screening of Obstructive Sleep Apnea Syndrome by Electronic-Nose Analysis of Volatile Organic Compounds

Obstructive Sleep Apnea Syndrome (OSAS) carries important social and economic implications. Once the suspicion of OSAS has arisen, Polysomnography (PSG) represents the diagnostic gold standard. However, about 45% of people who have undergone PSG are free from OSAS. Thus, efforts should be made to improve the selection of subjects. We verified whether the pattern of Volatile Organic Compounds (VOCs) helps to select patients amenable to PSG. We studied 136 subjects (20 obese non-OSAS, 20 hypoxic OSAS, 20 non-hypoxic OSAS, and 20 non-hypoxic Chronic Obstructive Pulmonary Disease (COPD) vs 56 healthy controls) without any criteria of exclusion for comorbidity to deal with a real-life population. VOCs patterns were analyzed using electronic-nose (e-nose) technology. A Discriminant Analysis (Partial Least Square-Discriminant Analysis) was performed to predict respiratory functions and PSG parameters. E-nose distinguished controls (100% correct classification) from others and identified 60% of hypoxic, and 35% of non-hypoxic OSAS patients. Similarly, it identified 60% of COPD patients. One-by-one group comparison yielded optimal discrimination of OSAS vs controls and of COPD vs controls (100% correct classification). In conclusion, e-nose technology applied to breath-analysis can discriminate non-respiratory from respiratory diseased populations in real-life multimorbid populations and exclude OSAS. If confirmed, this evidence may become pivotal for screening purposes.

A European Respiratory Society technical standard: exhaled biomarkers in lung disease

Breath tests cover the fraction of nitric oxide in expired gas (F_eNO), volatile organic compounds (VOCs), variables in exhaled breath condensate (EBC) and other measurements. For EBC and for F_eNO, official recommendations for standardised procedures are more than 10 years old and there is none for exhaled VOCs and particles. The aim of this document is to provide technical standards and recommendations for sample collection and analytic approaches and to highlight future research priorities in the field. For EBC and F_eNO, new developments and advances in technology have been evaluated in the current document. This report is not intended to provide clinical guidance on disease diagnosis and management.Clinicians and researchers with expertise in exhaled biomarkers were invited to participate. Published studies regarding methodology of breath tests were selected, discussed and evaluated in a consensus-based manner by the Task Force members.Recommendations for standardisation of sampling, analysing and reporting of data and suggestions for research to cover gaps in the evidence have been created and summarised.Application of breath biomarker measurement in a standardised manner will provide comparable results, thereby facilitating the potential use of these biomarkers in clinical practice.

Electronic Nose Technology in Respiratory Diseases

Electronic noses (e-noses) are based on arrays of different sensor types that respond to specific features of an odorant molecule, mostly volatile organic compounds (VOCs). Differently from gas chromatography and mass spectrometry, e-noses can distinguish VOCs spectrum by pattern recognition. E-nose technology has successfully been used in commercial applications, including military, environmental, and food industry. Human-exhaled breath contains a mixture of over 3000 VOCs, which offers the postulate that e-nose technology can have medical applications. Based on the above hypothesis, an increasing number of studies have shown that breath profiling by e-nose could play a role in the diagnosis and/or screening of various respiratory and systemic diseases. The aim of the present study was to review the principal literature on the application of e-nose technology in respiratory diseases.

Breath-print analysis by e-nose may refine risk stratification for adverse outcomes in cirrhotic patients

BACKGROUND & AIMS

The spectrum of volatile organic compounds in the exhaled breath (breath-print, BP) has been shown to characterize patients with cirrhosis and with worse hepatic function. However, the association of different BPs with clinically relevant outcomes has not been described yet. Hence, we aimed to evaluate the association between BPs, mortality and hospitalization in cirrhotic patients and to compare it with that of the "classical" prognostic indices (Child-Pugh Classification [CPC] and MELD).

METHODS

Eighty-nine cirrhotic patients (M/F 59/30, mean age 64.8 ± 11.3, CPC A/B/C 37/33/19) were recruited and followed up for a median time of 23 months. Clinical and biochemical data were collected. Breath collection and analysis were obtained through Pneumopipe^® and BIONOTE e-nose respectively.

RESULTS

Four different BP clusters (A, B, C, D) were identified. BP clusters A and D were associated with a significantly increased risk of mortality (HR 2.9, 95% confidence intervals [CI] 1.5-5.6) and hospitalization (HR 2.6, 95% CI 1.4-4.6), even in multiple adjusted models including CPC and MELD score (adjusted [a]HR 2.8, 95% CI 1.1-7.0 for mortality and aHR 2.2, 95% CI 1.1-4.2 for hospitalization). CPC C maintained the strongest association with both mortality (aHR 17.6, 95% CI 1.8-174.0) and hospitalization (aHR 12.4, 95% CI 2.0-75.8).

CONCLUSIONS

This pilot study demonstrates that BP clusters are associated with significant clinical endpoints (mortality and hospitalization) even independently from "classical" prognostic indices. Even though further studies are warranted on this topic, our findings suggest that the e-nose may become an adjunctive aid to stratify the risk of adverse outcomes in cirrhotic patients.

Breath-print analysis by e-nose for classifying and monitoring chronic liver disease: a proof-of-concept study

Since the liver plays a key metabolic role, volatile organic compounds in the exhaled breath might change with type and severity of chronic liver disease (CLD). In this study we analysed breath-prints (BPs) of 65 patients with liver cirrhosis (LC), 39 with non-cirrhotic CLD (NC-CLD) and 56 healthy controls by the e-nose. Distinctive BPs characterized LC, NC-CLD and healthy controls, and, among LC patients, the different Child-Pugh classes (sensitivity 86.2% and specificity 98.2% for CLD vs healthy controls, and 87.5% and 69.2% for LC vs NC-CLD). Moreover, the area under the BP profile, derived from radar-plot representation of BPs, showed an area under the ROC curve of 0.84 (95% CI 0.76–0.91) for CLD, of 0.76 (95% CI 0.66–0.85) for LC, and of 0.70 (95% CI 0.55–0.81) for decompensated LC. By applying the cut-off values of 862 and 812, LC and decompensated LC could be predicted with high accuracy (PPV 96.6% and 88.5%, respectively). These results are proof-of-concept that the e-nose could be a valid non-invasive instrument for characterizing CLD and monitoring hepatic function over time. The observed classificatory properties might be further improved by refining stage-specific breath-prints and considering the impact of comorbidities in a larger series of patients.

Volatile signature for the early diagnosis of lung cancer

Exhaled breath contains hundreds of volatile organic compounds (VOCs). Several independent researchers point out that the breath of lung cancer patients shows a characteristic VOC-profile which can be considered as lung cancer signature and, thus, used for diagnosis. In this regard, the analysis of exhaled breath with gas sensor arrays is a potential non-invasive, relatively low-cost and easy technique for the early detection of lung cancer. This clinical study evaluated the gas sensor array response for the identification of the exhaled breath of lung cancer patients. This study involved 146 individuals: 70 with lung cancer confirmed by computerized tomography (CT) or positron emission tomography-(PET) imaging techniques and histology (biopsy) or with clinical suspect of lung cancer and 76 healthy controls. Their exhaled breath was measured with a gas sensor array composed of a matrix of eight quartz microbalances (QMBs), each functionalized with a different metalloporphyrin. The instrument produces, for each analyzed sample, a vector of signals encoding the breath (breathprint). Breathprints were analyzed with multivariate analysis in order to correlate the sensor signals to the disease. Breathprints of the lung cancer patients were differentiated from those of the healthy controls with a sensitivity of 81% and specificity of 91%. Similar values were obtained in patients with and without metabolic comorbidities, such as diabetes, obesity and dyslipidemia (sensitivity 85%, specificity 88% and sensitivity 76%, specificity 94%, respectively). The device showed a large sensitivity to lung cancer at stage I with respect to stage II/III/IV (92% and 58% respectively). The sensitivity for stage I did not change for patients with or without metabolic comorbidities (90%, 94%, respectively). Results show that this electronic nose can discriminate the exhaled breath of the lung cancer patients from those of the healthy controls. Moreover, the largest sensitivity is observed for the subgroup of patients with a lung cancer at stage I.

BIONOTE e-nose technology may reduce false positives in lung cancer screening programmes†

OBJECTIVES

Breath composition may be suggestive of different conditions. E-nose technology has been used to profile volatile organic compounds (VOCs) pattern in the breath of patients compared with that of healthy individuals. BIOsensor-based multisensorial system for mimicking NOse, Tongue and Eyes (BIONOTE) technology differs from Cyranose® based on a set of separate transduction features. On the basis of our previously published experience, we investigated the discriminating ability of BIONOTE in a high-risk population enrolled in a lung cancer screening programme.

METHODS

One hundred individuals were selected for BIONOTE based on the attribution to the high-risk category (i.e. age, smoking status, chronic obstructive pulmonary disease status) of the University Campus Bio-Medico lung screening programme. We used a measure chain consisting of (i) a device named Pneumopipe (EU patent: EP2641537 (A1):2013-09-25) able to catch exhaled breath by an individual normally breathing into it and collect the exhalate onto an adsorbing cartridge; (ii) an apparatus for thermal desorption of the cartridge into the sensors chamber and (iii) a gas sensor array which is part of a sensorial platform named BIONOTE for the VOCs mixture analysis. Partial least square (PLS) has been used to build up the model, with Leave-One-Out cross-validation criterion. Each breath fingerprint analysis costs €10.

RESULTS

The overall sensitivity and specificity were 86 and 95%, respectively, delineating a substantial difference between patients and healthy individuals.

CONCLUSIONS

Our preliminary data show that BIONOTE technology may be used to reduce false-positive rates resulting from lung cancer screening with low-dose computed tomography in a cost-effective fashion. The model will be tested on a larger number of patients to confirm the reliability of these results.

A smart pill for drug delivery with sensing capabilities

In this paper a novel system for local drug delivery is described. The actuation principle of the micropump used for drug delivery relies on the electrolysis of a water-based solution, which is separated from a drug reservoir by an elastic membrane. The electrolytically produced gases pressurize the electrolytic solution reservoir, causing the deflection of the elastic membrane. Such deflection, in turn, forces the drug out of its reservoir through a nozzle. The proposed system is integrated in a swallowable capsule, equipped with an impedance sensor useful to acquire information on the physiological conditions of the tissue. Such information can be used to control pump activation.

Exhaled breath analysis by electronic nose in respiratory diseases

Breath analysis via electronic nose is a technique oriented around volatile organic compound (VOC) profiling in exhaled breath for diagnostic and prognostic purposes. This approach, when supported by methodologies for VOC identification, has been often referred to as metabolomics or breathomics. Although breath analysis may have a substantial impact on clinical practice, as it may allow early diagnosis and large-scale screening strategies while being noninvasive and inexpensive, some technical and methodological limitations must be solved, together with crucial interpretative issues. By integrating a review of the currently available literature with more speculative arguments about the potential interpretation and application of VOC analysis, the authors aim to provide an overview of the main relevant aspects of this promising field of research.

Prostate cancer diagnosis through electronic nose in the urine headspace setting: a pilot study

BACKGROUND

To evaluate the efficacy of prostate cancer (PCa) detection by the electronic nose (EN) on human urine samples.

METHODS

Urine samples were obtained from candidates of prostate biopsy (PB). Exclusion criteria were a history of urothelial carcinoma or other malignant disease, urine infection, fasting for <12 h before PB or ingestion of alcohol or foods that might alter the urine smell in the last 24 h. The initial part of the voided urine and the midstream were collected separately in two sterile containers. Both samples were analyzed by the EN immediately after the collection. All patients underwent a standard transperineal, transrectal-ultrasound-guided PB. The pathological results were compared with the outcomes of the EN. Sensitivity and specificity of EN were assessed.

RESULTS

Forty-one men were included in the study. Fourteen out of the 41 patients were positive for PCa. Midstream urine did not correlate significantly neither with a positive nor with a negative PB. Instead, significantly different results on the initial part of the urine stream between positive and negative PBs were obtained. The EN correctly recognized 10 out of the 14 cases (that is, sensitivity 71.4% (confidence interval (CI) 42-92%)) of PCa while four were false negatives. Moreover, the device recognized as negative 25 out of the 27 (that is, specificity 92.6% (CI 76-99%)) samples of negative PBs, with only two false positives.

CONCLUSIONS

We believe this is the first demonstration of an olfactory imprinting of the initial part of the urine stream in patients with PCa that was revealed by an EN, with high specificity.

Chronic Obstructive Pulmonary Disease in the elderly

The prevalence of Chronic Obstructive Pulmonary Disease (COPD) dramatically increases with age, and COPD complicated by chronic respiratory failure may be considered a geriatric condition. Unfortunately, most cases remain undiagnosed because of atypical clinical presentation and difficulty with current respiratory function diagnostic standards. Accordingly, the disease is under-recognized and undertreated. This is expected to impact noticeably the health status of unrecognized COPD patients because a timely therapy could mitigate the distinctive and important effects of COPD on the health status. Comorbidity also plays a pivotal role in conditioning both the health status and the therapy of COPD besides having major prognostic implication. Several problems affect the overall quality of the therapy for the elderly with COPD, and current guidelines as well as results from pharmacological trials only to some extent apply to this patient. Finally, physicians of different specialties care for the elderly COPD patient: physician's specialty largely determines the kind of approach. In conclusion, COPD, in itself a complex disease, becomes difficult to identify and to manage in the elderly. Interdisciplinary efforts are desirable to provide the practicing physician with a multidisciplinary guide to the identification and treatment of COPD.

Detection and identification of cancers by the electronic nose

INTRODUCTION

The early determination of serious pathologies has so far been an important issue in both the medical and social fields. The search for an instrument able to detect cancers has led to the consideration of the usage of chemicals of the human body, which carry, through its volatile compounds, information coming from or related to defined pathologies.

AREAS COVERED

The electronic nose (EN) seems to represent a good solution for the detection of cancers of different types. Recent results showed the utility of an EN to smell chemicals related to lung, melanoma, prostatic, breast and pancreatic cancers. The results obtainable from ENs are chemical images and, as it will be shown in this paper, the probability of cancer recognition is rather high. Main results obtained at international level and by the authors of this paper will be commented upon.

EXPERT OPINION

A personal opinion is given trying to foresee future developments of the olfaction strategy. To this purpose, two main aspects are considered: looking for better overall stability of the EN and for a new use of ENs in detecting alterations between blood and pathology components.

Electronic nose and GC-MS analysis of volatile compounds in Tuber magnatum Pico: evaluation of different storage conditions

The characteristic aromatic composition of white truffles (Tuber magnatum Pico) determines its culinary and commercial value. However modifications of truffle organoleptic proprieties occur during preservation. A study of headspace of white truffles by using Electronic nose (E-nose), gas chromatography-mass spectrometry (GC-MS) and sensory analyses was performed. Truffles were stored at different conditions for 7 days: +4 and +8°C wrapped in blotting paper or covered by rice or none of the above. Headspace E-nose measurements and sensory analyses were performed each day. Statistical multivariate analysis of the data showed the capability of E-nose to predict sensorial analysis scores and to monitor aroma profile changes during storage. Truffle's volatile molecules were also extracted by headspace solid phase microextraction technique and separated and identified by GC-MS. Partial Components Analysis of data was performed. E-nose and GC-MS results were in agreement and showed that truffle storage in paper at +8°C seemed to be the best storage condition.

Diagnostic performance of an electronic nose, fractional exhaled nitric oxide, and lung function testing in asthma

BACKGROUND

Analysis of exhaled breath by biosensors discriminates between patients with asthma and healthy subjects. An electronic nose consists of a chemical sensor array for the detection of volatile organic compounds (VOCs) and an algorithm for pattern recognition. We compared the diagnostic performance of a prototype of an electronic nose with lung function tests and fractional exhaled nitric oxide (FENO) in patients with atopic asthma.

METHODS

A cross-sectional study was undertaken in 27 patients with intermittent and persistent mild asthma and in 24 healthy subjects. Two procedures for collecting exhaled breath were followed to study the differences between total and alveolar air. Seven patients with asthma and seven healthy subjects participated in a study with mass spectrometry (MS) fingerprinting as an independent technique for assessing between group discrimination. Classification was based on principal component analysis and a feed-forward neural network.

RESULTS

The best results were obtained when the electronic nose analysis was performed on alveolar air. Diagnostic performance for electronic nose, FENO, and lung function testing was 87.5%, 79.2%, and 70.8%, respectively. The combination of electronic nose and FENO had the highest diagnostic performance for asthma (95.8%). MS fingerprints of VOCs could discriminate between patients with asthma and healthy subjects.

CONCLUSIONS

The electronic nose has a high diagnostic performance that can be increased when combined with FENO. Large studies are now required to definitively establish the diagnostic performance of the electronic nose. Whether this integrated noninvasive approach will translate into an early diagnosis of asthma has to be clarified.

TRIAL REGISTRATION

EUDRACT https://eudralink.emea.europa.eu; Identifier: 2007-000890-51; and clinicaltrials.gov; Identifier: NCT00819676.

An investigation on electronic nose diagnosis of lung cancer

The use of gas sensor arrays as medical diagnosis instruments has been proposed several years ago. Since then, the idea has been proven for a limited number of diseases. The case of lung cancer is particularly interesting because it is supported by studies that have shown the correlation between the composition of breath and the disease. However, it is known that many other diseases can alter the breath composition, so for lung cancer diagnosis it is necessary not only to detect generic alterations but those specifically consequent to cancer. In this paper an experiment, performed in the bronchoscopy unit of a large hospital, aimed at discriminating between lung cancer, diverse lung diseases and reference controls is illustrated. Results show not only a satisfactory identification rate of lung cancer subjects but also a non-negligible sensitivity to breath modification induced by other affections. Furthermore, the effects of some compounds frequently found in the breath of lung cancer subjects have also been studied. Results indicate that breath samples of control individuals drift towards the lung cancer group when added with either single or mixtures of these alleged cancer-related compounds.

Application of a quartz microbalance based gas sensor array for the study of halitosis

Research into the monitoring and control of oral malodor has nowadays received new stimulus from the importance gained by this phenomenon as a medical and social problem. In this paper the performance of an electronic nose to detect this manifestation has been investigated in order to explore the possibility of using this instrument as a complement to those already existing for the assessment of oral malodor. In particular, a breath sampling procedure has been optimized to maximize the transfer to the sensors of those molecules that are known to be associated with the malodor. The sensitivity of electronic nose sensors to hydrogen sulfide, butyric acid and valeric acid-three compounds known to play a major role in halitosis-has been measured and the results indicate that the threshold limits are compatible with halitosis detection. An experiment with real and artificial samples indicates the possibility of identifying halitosis-affected individuals and of discriminating them according to breath composition.

Fish freshness detection by a computer screen photoassisted based gas sensor array

In the last years a large number of different measurement methodologies were applied to measure the freshness of fishes. Among them the connection between freshness and headspace composition has been considered by gas chromatographic analysis and from the last two decades by a number of sensors and biosensors aimed at measuring some characteristic indicators (usually amines). More recently also the so-called artificial olfaction systems gathering together many non-specific sensors have shown a certain capability to transduce the global composition of the fish headspace capturing the differences between fresh and spoiled products. One of the main objectives related to the introduction of sensor systems with respect to the analytical methods is the claimed possibility to distribute the freshness control since sensors are expected to be "portable" and "simple". In spite of these objectives, until now sensor systems did not result in any tool that may be broadly distributed. In this paper, we present a chemical sensor array where the optical features of layers of chemicals, sensitive to volatile compounds typical of spoilage processes in fish, are interrogated by a very simple platform based on a computer screen and a web cam. An array of metalloporphyrins is here used to classify fillets of thawed fishes according to their storage days and to monitor the spoilage in filleted anchovies for a time of 8 h. Results indicate a complete identification of the storage days of thawed fillets and a determination of the storage time of anchovies held at room temperature with a root mean square error of validation of about 30 min. The optical system produces a sort of spectral fingerprint containing information about both the absorbance and the emission of the sensitive layer. The system here illustrated, based on computer peripherals, can be easily scaled to any device endowed with a programmable screen and a camera such as cellular phones offering for the first time the possibility to fulfil the sensor expectation of diffused and efficient analytical capabilities.