Analysis Of Exhaled Air Research Articles

Use of Respiratory Volatile Organic Compounds in the Diagnosis of Infections

Introduction: Infectious diseases continue to significantly affect global human health. Conducting infection diagnostic tests can be difficult due to limited resources, time limitations, or the inadequacy of current diagnostic techniques. There is a growing interest in developing diagnostic methods through the analysis of exhaled air, as breath sampling is non-invasive, safe, and convenient. Volatile organic compounds (VOCs) present in exhaled air provide insights into the metabolic and biophysical processes associated with various diseases. This review highlights recent advancements in breath-based diagnosis for respiratory infections, including those caused by the influenza virus, SARS-CoV-2, Mycobacterium tuberculosis, Pseudomonas aeruginosa, and Aspergillus fumigatus. Furthermore, this review also examines the contemporary viewpoint on diagnosing two significant infections: Helicobacter pylori and malaria. Conclusion: Certain volatile organic compounds (VOCs) linked to respiratory conditions are specifically and often associated with multiple infectious diseases, indicating that breath analysis could be a valuable approach for creating diagnostic tools. However, existing challenges encompass the absence of standardized protocols for collecting and analyzing breath samples, as well as a deficiency in validation studies. Additional research is essential to broaden the use of breath analysis in clinical practice.

Express analysis of acetone in exhaled air for diagnosing diabetes melli-tus

Exhaled air analysis is an actively developing area of medical non-invasive diagnostics, as it does not involve invasive interventions and can be performed repeatedly. It is known that acetone in exhaled air correlates with blood glucose and is a biomarker of diabetes. The use of analytical systems to analyse acetone in exhaled air in medical institutions will allow for the timely diagnosis of pathological changes in blood glucose levels, the early diagnosis of diabetes, and the monitoring of the effectiveness of treatments. In this study, we described the express analysis of acetone in exhaled air using a mobile diagnostic complex based on microfluidic systems including a PIA gas microchromatograph with a thermochemical detector, a planar chromatographic column, a thermostatically controlled system for the sampling and selective capture of interfering components, operated by electric microvalves, and an automatic dosing system with adjustable blowdown from 0.1 to 5 sec and specialised software. We proposed using a diagnostically significant range of concentrations: from 0.5 ppm to 20 ppm of acetone in exhaled air in the diagnosis of diabetes. The total analysis time is 3 min, retention time for acetone is 60 sec. Testing of the complex confirmed that it allows for the direct determination of acetone in exhaled air. The use of the capture and drying system prevents the loss of the target substance and ensures good convergence of the results. The deviation from the reference value does not exceed 10%. Field testing confirmed the data obtained on model mixtures. The developed mobile diagnostic complex with automatic programmed dosing and the technique for the quantitative determination of acetone in exhaled air (0.5-20 ppm) can be recommended for use in clinical studies in medical institutions.

Analysis of the most popular online BAC calculators = Analiza najpopularniejszych dostępnych w sieci „kalkulatorów trzeźwości”

In order to check their sobriety after drinking alcohol, drivers can use applications available online that perform prospective estimation of alcohol content, called ‘alcomat online’ or ‘BA C calculators’. The aim of the study was to analyse the method of performing calculations using ‘BA C calculators’ available on the Internet and to assess their reliability. The five most popular ‘calculators’ found in the Google search engine and a commercial one were analysed. The applications were tested by entering data on 10 cases of alcohol consumption by people were tested for alcohol content in exhaled air using the Alcotest 7510 analyser and alcohol curves were plotted for them. Then, real ethanol concentrations and complete ethanol elimination times for these people were compared with values calculated by the applications. The analysed ‘calculators’ base their calculations on various principles. Both the maximum alcohol concentrations and the time of their occurrence varied among the applications, but all seem to use the alcohol distribution coefficient established by Widmark. The use of individual elimination rates ranging from 0.12 to even 0.3‰/h was also observed. The time for complete alcohol elimination indicated by the applications was in most cases longer than the actual time. Online applications such as the ‘BA C calculator’ available to Polish users may be helpful tools for determining the time of complete elimination of alcohol from the body. However, due to the different calculation methods used in applications, which sometimes lead to different conclusions, they should be approached with great caution. These applications will not replace reliable sobriety tests, e.g. analysis of exhaled air.

Validation of an alternative technique for RQ estimation in anesthetized pigs

BackgroundRespiratory quotient (RQ) is an important variable when assessing metabolic status in intensive care patients. However, analysis of RQ requires cumbersome technical equipment. The aim of the current study was to examine a simplified blood gas-based method of RQ assessment, using Douglas bag measurement of RQ (Douglas-RQ) as reference in a laboratory porcine model under metabolic steady state. In addition, we aimed at establishing reference values for RQ in the same population, thereby generating data to facilitate further research.MethodsRQ was measured in 11 mechanically ventilated pigs under metabolic steady state using Douglas-RQ and CO-oximetry blood gas analysis of pulmonary artery and systemic carbon dioxide and oxygen content. The CO-oximetry data were used to calculate RQ (blood gas RQ). Paired recordings with both methods were made once in the morning and once in the afternoon and values obtained were analyzed for potential significant differences.ResultsThe average Douglas-RQ, for all data points over the whole day, was 0.97 (95%CI 0.95–0.99). The corresponding blood gas RQ was 0.95 (95%CI 0.87–1.02). There was no statistically significant difference in RQ values obtained using Douglas-RQ or blood gas RQ for all data over the whole day (P = 0.43). Bias was − 0.02 (95% limits of agreement ± 0.3). Douglas-RQ decreased during the day 1.00 (95%CI 0.97–1.03) vs 0.95 (95%CI 0.92–0.98) P < 0.001, whereas the decrease was not significant for blood gas RQ 1.02 (95%CI 0.89–1.16 vs 0.87 (0.80–0.94) P = 0.11.ConclusionRQ values obtained with blood gas analysis did not differ statistically, compared to gold standard Douglas bag RQ measurement, showing low bias but relatively large limits of agreement, when analyzed for the whole day. This indicates that a simplified blood gas-based method for RQ estimations may be used as an alternative to gold standard expired gas analysis on a group level, even if individual values may differ. In addition, RQ estimated with Douglas bag analysis of exhaled air, was 0.97 in anesthetized non-fasted pigs and decreased during prolonged anesthesia.

The effect of voluntary hypoventilation in yoga breathing exercises on gas exchange and EEG activity in healthy trained subjects

Objective: to assess the effect of voluntary hypoventilation during yoga breathing exercises on gas exchange and EEG activity in a group of healthy, trained practitioners.Materials and methods: 25 volunteers (21 men and 4 women, average age 42.96 ± 9.19 years) performed hypoventilation yoga exercises with a decrease in respiratory rate to 1–1.5 times/minute. Registration of respiratory rate, tidal volume and minute volume of breathing, gas analysis of exhaled air (PetCO2, FeO2) and spectral analysis of electroencephalogram (EEG) in gICA model were carried out during breathing with a frequency of 1–1.5 times/minute and during relatively free breathing with mental calculation.Results: Breathing with a frequency of 1–1.5 times/minute causes a decrease in minute volume of breathing, the development of alveolar hypoxia and hypercapnia, which leads to an increase in the power of some local components in the slow delta, theta and alpha EEG bands. In addition, breathing with a frequency of 1–1.5 times/minute is accompanied by a decrease in the alpha- and beta-power of some components, the sources of which are located in the motor areas of the cortex, but is also accompanied by an increase in the power of components with widespread scalp topography in beta and gamma bands.Conclusion: Voluntary hypoventilation during yoga breathing exercises leads to the development of alveolar hypoxia and hypercapnia, accompanied by an increase in the power of local components in the slow EEG bands. At the same time, the alpha and beta powers of components localized in the motor areas of the cortex decrease, which may be a consequence of muscle tension during slow breathing.

Analysis of Volatile Organic Compounds in Exhaled Air in Patients with Sickle Cell Disease during Vaso-Occlusive Episodes

Background: Sickle cell disease (SCD) is an inherited red blood cell disorder characterized by hemolytic anemia, inflammation and vaso-occlusion. Due to the process of vaso-occlusion patients with SCD experience unpredictable and painful vaso-occlusive episodes (VOE), causing stress and disruption of daily life. To date, we lack adequate markers to predict the development of a VOE before it occurs. In other conditions such as asthma, exhaled air analyses have shown to be of diagnostic value and may predict exacerbations. In the human body, metabolic processes generate volatile organic compounds, that are first released into the blood, and then exhaled by the lungs. As a result, exhaled air consists of several volatile, organic compounds that may reflect pathophysiological disease processes. As we presently lack urgently needed biomarkers to predict VOEs, the aim of this study was to identify distinctive volatile organic compounds in exhaled air (eVOC) during VOE in patients with SCD, that may serve as predictors of VOE when detected in low quantities as a VOE is evolving. Methods: In this longitudinal, observational single center cohort study, patients with SCD aged 6 years or older were eligible if they were hospitalized for a VOE at Amsterdam University Medical Centers between October 2021 and March 2023. Following informed consent, an exhaled air sample was taken during hospitalization, and one at least 4 weeks after discharge from the hospital (steady state). Clinical data were collected from medical files including demographics, medical history, medication use and laboratory values during steady state, and during hospitalization for VOE. Patients were instructed not to eat, drink or take medication orally 2 hours prior to the measurements. Exhaled air samples were collected in Nalophan bags, and the eVOCs were transferred to stainless steel thermal desorption tubes filled with Tenax GR for analysis by gas chromatography-mass spectrometry. The Wilcoxon signed-rank test was used to test for differences in eVOCs between VOE and steady state. Significantly different eVOCs were tentatively identified by linking raw chromatograms to corresponding metabolites based on NIST-library matching. The significance level was set to 0.05. All analyses were performed using R Studio (version 1.3.1093) software. Results: In total, 25 patients with SCD were included in this study, providing 71 exhaled air samples. The mean age at inclusion was 25.7 years (SD ±10.2). The majority of the participants had SCD genotype HbSS (60%). At time of exhaled air measurement during hospitalization, participants had symptoms for the median number of 1 day (IQR 0.5-3), and the median pain score was 6 out of 10 (IQR 3-7). A total of 58 different fragments could be identified between VOE and steady state (Wilcoxon rank p&amp;lt; 0.05), representing 26 unique eVOCs. The majority of these eVOCs were alkanes, alkenes, and esters. A representing compound for each chemical group is shown in Figure 1. In the majority of the patients, cyclohexane,1,2,4-trimethyl and propanoic acid, ethyl ester were upregulated during VOE, while 1-propene, 2-methyl- was downregulated. Conclusion: This pilot study identified 26 compounds in exhaled air that differentiated VOE from steady state in patients with SCD. Thus, analysis of exhaled air could serve as a promising, non-invasive and patient-friendly biomarker to predict VOE in SCD. Further identification of the discriminative compounds in exhaled air could provide valuable insights into the metabolic processes during VOE.

Accuracy calibration transfer between multi-sensor systems based on metal-oxide gas sensors used for analysis of exhaled air

The application of electronic nose system as an instrument for exhaled air analysis for diagnosing various diseases (lung cancer, etc.) is one of the most rapidly developing areas of predictive medicine. However, a significant disadvantage of such systems is difficulty in production of identical multi-sensor systems because the sensors of the same type are not identical, that degrades the predictive ability. To solve this problem calibration transfer methods are used.This paper analyzes currently applied calibration transfer methods. A new approach to evaluate the effectiveness of calibration transfer methods for two multi-sensor systems is proposed and implemented. One- and three-component gas mixtures are taken for the analysis. In this work, four methods are used to adjust the sensor responses: UDS, UDSwoi, DS-L1R and DS-PLS2. Applicability of one-factor standardization methods (UDS and UDSwoi) is shown on the classification tasks: multi-class classification task of one-component gas mixtures and binary classification task of three-component gas mixtures. Multi-class classification of model one-component gas mixtures for UDS, UDSwoi with 4 calibration transfer samples provided the classification accuracy of 0.985 and 0.990, respectively. The binary classification of two three-component mixtures with different ratios of three VOCs within the 20% discrepancy limits, UDS, UDSwoi and DS-PLS2 achieved an error-free accuracy of 1.000.

ИМПУЛЬСНАЯ ФУРЬЕ-СПЕКТРОСКОПИЯ ДЛЯ АНАЛИТИЧЕСКИХ ПРИЛОЖЕНИЙ

The review of pulsed Fourier spectroscopy methods including the pioneer works (Ekkers and Flygare etc.), and new trends in development of this approach with the nonstationary gas spectroscopy methods in particularly are presented in this work. In particular, such radiation sources as quantum-cascade lasers (QCLs) in the terahertz (THz) frequency range, which make it possible to implement the method of pulsed Fourier spectroscopy, are considered. The presented approach is promising for the development of non-invasive methods of medical diagnostics based on the metabolic analysis of exhaled air, the composition of biological fluids, including vapors and thermal decomposition products of biological fluids. Some examples of the application of non-stationary spectroscopic methods for the analysis of the composition of multicomponent gas mixtures of biological origin are presented.

The use of exhaled air analysis in discriminating interstitial lung diseases: a pilot study

BackgroundFibrotic Interstitial lung diseases (ILD) are a heterogeneous group of chronic lung diseases characterized by diverse degrees of lung inflammation and remodeling. They include idiopathic ILD such as idiopathic pulmonary fibrosis (IPF), and ILD secondary to chronic inflammatory diseases such as connective tissue disease (CTD). Precise differential diagnosis of ILD is critical since anti-inflammatory and immunosuppressive drugs, which are beneficial in inflammatory ILD, are detrimental in IPF. However, differential diagnosis of ILD is still difficult and often requires an invasive lung biopsy. The primary aim of this study is to identify volatile organic compounds (VOCs) patterns in exhaled air to non-invasively discriminate IPF and CTD-ILD. As secondary aim, the association between the IPF and CTD-ILD discriminating VOC patterns and functional impairment is investigated.MethodsFifty-three IPF patients, 53 CTD-ILD patients and 51 controls donated exhaled air, which was analyzed for its VOC content using gas chromatograph- time of flight- mass spectrometry.ResultsBy applying multivariate analysis, a discriminative profile of 34 VOCs was observed to discriminate between IPF patients and healthy controls whereas 11 VOCs were able to distinguish between CTD-ILD patients and healthy controls. The separation between IPF and CTD-ILD could be made using 16 discriminating VOCs, that also displayed a significant correlation with total lung capacity and the 6 min’ walk distance.ConclusionsThis study reports for the first time that specific VOC profiles can be found to differentiate IPF and CTD-ILD from both healthy controls and each other. Moreover, an ILD-specific VOC profile was strongly correlated with functional parameters. Future research applying larger cohorts of patients suffering from a larger variety of ILDs should confirm the potential use of breathomics to facilitate fast, non-invasive and proper differential diagnosis of specific ILDs in the future as first step towards personalized medicine for these complex diseases.

SERS Platform Based on Hollow-Core Microstructured Optical Fiber: Technology of UV-Mediated Gold Nanoparticle Growth.

Surface-enhanced Raman spectroscopy (SERS) is a powerful technique for biosensing. However, SERS analysis has several concerns: the signal is limited by a number of molecules and the area of the plasmonic substrate in the laser hotspot, and quantitative analysis in a low-volume droplet is confusing due to the change of concentration during quick drying. The usage of hollow-core microstructured optical fibers (HC-MOFs) is thought to be an effective way to improve SERS sensitivity and limit of detection through the effective irradiation of a small sample volume filling the fiber capillaries. In this paper, we used layer-by-layer assembly as a simple method for the functionalization of fiber capillaries by gold nanoparticles (seeds) with a mean diameter of 8 nm followed by UV-induced chloroauric acid reduction. We also demonstrated a simple and quick technique used for the analysis of the SERS platform formation at every stage through the detection of spectral shifts in the optical transmission of HC-MOFs. The enhancement of the Raman signal of a model analyte Rhodamine 6G was obtained using such type of SERS platform. Thus, a combination of nanostructured gold coating as a SERS-active surface and a hollow-core fiber as a microfluidic channel and a waveguide is perspective for point-of-care medical diagnosis based on liquid biopsy and exhaled air analysis.

Application of machine learning and laser optical-acoustic spectroscopy to study the profile of exhaled air volatile markers of acute myocardial infarction

Conventional acute myocardial infarction (AMI) diagnosis is quite accurate and has proved its effectiveness. However, despite this, discovering more operative methods of this disease detection is underway. From this point of view, the application of exhaled air analysis for a similar diagnosis is valuable. The aim of the paper is to research effective machine learning algorithms for the predictive model for AMI diagnosis constructing, using exhaled air spectral data. The target group included 30 patients with primary myocardial infarction. The control group included 42 healthy volunteers. The ‘LaserBreeze’ laser gas analyzer (Special Technologies Ltd, Russia), based on the dual-channel resonant photoacoustic detector cell and optical parametric oscillator as the laser source, had been used. The pattern recognition approach was applied in the same manner for the set of extracted concentrations of AMI volatile markers and the set of absorption coefficients in a most informative spectral range 2.900 ± 0.125 µm. The created predictive model based on the set of absorption coefficients provided 0.86 of the mean values of both the sensitivity and specificity when linear support vector machine (SVM) combined with principal component analysis was used. The created predictive model based on using six volatile AMI markers (C5H12, N2O, NO2, C2H4, CO, CO2) provided 0.82 and 0.93 of the mean values of the sensitivity and specificity, respectively, when linear SVM was used.

ЭКСПРЕСС-ДИАГНОСТИКА ЗАБОЛЕВАНИЙ ПО ВЫДЫХАЕМОМУ ВОЗДУХУ НА ОСНОВЕ КВАДРУПОЛЬНОГО МАСС-СПЕКТРОМЕТРА

The method is proposed for express diagnostics of diseases according to the data of mass spectrometric analysis of exhaled air. An algorithm for calculating the probability of diseases has been developed and tested. The results of data processing of patients treated in two oncological clinics are presented. The calculation of the probability of disease according to the data of mass spectrometric analysis of exhaled air is based on attributing the mass spectrum of the tested patient to the mass-spectra of the corresponding control group. Each control group is formed by collecting an array of spectra from at least ten patients with the same disease. Diagnostics is performed by transforming the matrix of spectra of the control group and the spectrum of a patient being tested into the space of the principal components. The probability of a disease is determined by the Euclidean distance of the patient's coordinates from the centroid of the control group in the multidimensional space of these principal components.

Exhaled air analysis for pulmonary arterial hypertension fingerprints identification

Abstract Background Pulmonary arterial hypertension (PAH) is a rare disease which is often diagnosed in the late phase as its symptoms are non-specific and there is a lack of screening tests. Therefore, there is a strong need for identifying of its biomarkers. Aim To identify the biomarkers for PAH in the exhaled breath and in the serum. Methods The breath phase of all the patients was collected on the highly porous aseptic material by the use of special patented holder PL 232911. The collected air was then examined with gas chromatography mass spectrometry (GC/MS). For the control of the obtained results plasma of all the patients was examined by the use of Ultra High Performance Liquid Chromatography (UHPLC). A group of 10 patients (2 men, 8 women, mean age 60.4±10.9 years, BMI 27.6±6.0 kg/m2) with diagnosed PAH as well as the group of 10 healthy persons (6 men, 4 women, mean age 35±11 years, BMI 25.6±6.0 kg/m2) were enrolled into the study. Results The obtained spectral and chromatographic results clearly presents the qualitative and quantitative QA/QC sensitivity to the metabolites changes in the patient's breath. The identification of changes in ratio of the whole spectra of biomarkers can allow to obtain a multi-dimensional pathways for PAH diagnostics fig. 1. The chromatography data from patients suffering from PAH have been processed by the aid of signal processing toolbox in MATLAB. Only the peaks of the prominence of at least 10000 (experimentally established) have been taken under consideration. The prominence of a peak measures how much the peak stands out due to its intrinsic height and its location relative to other peaks. Next, for the each found peak the arguments of the two neighboring local minima, have been determined and the integration range for calculating the area under the each peak have been established. The ratio of the area under the significant peak to its prominence have been applied for further analysis. Conclusions Based on our preliminary results it seems that our method is specific and sensitive in the range of selected bio-fingerprints in patients with PAH. If confirmed on larger population the molecular level breath analysis can be used as a screening test as well as complementary diagnostic method in PAH to the standard clinical practice. Figure 1. The chromatograms of representative spectra for patients suffering from PAH (red), control (blue) with distinguished significant peaks (presented in the magnification according to their prominence). On the right side, there are the graphical presentation (area/prominence for peaks) of arbitrary chosen patient, but with reference to the original data and for two data approximations obtained by the DWT, which are important in the case of weak separated peaks. Funding Acknowledgement Type of funding source: Public Institution(s). Main funding source(s): University of Silesia in Katowice

METHODS FOR EARLY DETECTION OF LUNG CANCER (REVIEW)

Objective : to generalize the world experience of lung cancer screening using modern diagnostic methods. Material and Methods . Literature search was performed in Medline, Cochrane Library, Elibrary, PubMed systems, including publications describing the current capabilities of laboratory, instrumental and molecular genetic methods for early diagnosis of lung cancer, 58 of which were used to write this review. Results . The review highlighted the results of international randomized trials of lung cancer screening using sputum Cytology and low-dose computed tomography. Special attention was paid to the description of modern molecular and genetic biomarkers of lung cancer, such as epigenetic markers, microRNAs, the use of proteomics technology, metabolomics, microbiome research, and biomarkers from liquid biopsy. The analysis of the world literature confirming the prospects of methods of non-invasive diagnostics of tumor processes based on the analysis of exhaled air was carried out. Conclusion . The use of modern screening methods will significantly improve the effectiveness of early diagnosis and, as a result, cancer treatment. Starting treatment at an early stage can significantly increase the patient’s chances of recovery and faster social and labor adaptation. As a non – invasive method of cancer diagnosis, an electronic nose can act as a set of gas sensors and a certain method of information processing. An electronic nose based on relatively cheap gas sensors has comparable accuracy, ease of data collection, mobility, and other advantages compared to the above mentioned devices.

Diagnosis of Diabetes Based on Analysis of Exhaled Air by Terahertz Spectroscopy and Machine Learning

Results of studying the exhaled air of patients with diabetes mellitus in comparison with healthy volunteers with the use of broadband terahertz time-domain spectroscopy are presented. Typical spectral subranges in which absorption spectrum profiles of breath tests of the target and control group differ most significantly are revealed: 0.560, 0.738, 0.970, 1.070, 1.140, 1.180, and 1.400 THz. Using the principal component analysis, it is shown that the set of absorption coefficients in these regions allows one to reliably separate the target and control groups. The obtained results are compared with measurements of acetone vapors in the exhaled air of patients with diabetes mellitus and healthy volunteers.

Breath Semiconductor Metal Oxide Gas Detector using Arduino Nano

Interest in the research of small-sized semiconductor gas sensors for medical applications has sharply increased in recent years. Requirements for such sensors are their high sensitivity, performance, and stability to low concentrations of gases, mainly exhaled by a living organism. One of the most important directions of modern medicine is non-invasive diagnostics of the patients, based on the analysis of exhaled air in a special device. Exhaled breath contains about 1000 volatile organic compounds (VOCs) that are the products of metabolism.

Breath Semiconductor Metal Oxide Gas Detector using Arduino Nano

Interest in the research of small-sized semiconductor gas sensors for medical applications has sharply increased in recent years. Requirements for such sensors are their high sensitivity, performance, and stability to low concentrations of gases, mainly exhaled by a living organism. One of the most important directions of modern medicine is non-invasive diagnostics of the patients, based on the analysis of exhaled air in a special device. Exhaled breath contains about 1000 volatile organic compounds (VOCs) that are the products of metabolism.

Development of a new system to collect and dry patient exhalation samples for laser photo-acoustic gas analyzer.

The present work is devoted to the development of a new system for collecting and drying patient exhalation samples for a laser photo-acoustic gas analyzer for express analysis of exhaled air, as well as the possibility of ozone sterilization of the gas tract after use. It is proposed to collect the patient's exhalation in a disposable sterile plastic bag, place it in a low-temperature freezer chamber to freeze the water vapor, and then transfer part of the dried exhaled sample to the gas analyzer using a disposable syringe. It is proposed to use ozone purge for 10-15min to sterilize the gas path. Experimentally, it is shown that the water vapor content in the exhalation samples decreased by ~ 20 times when the packet with samples was kept at a temperature of - 18°C during 10min. Cooling the exhalation sample in the packet to -45°С and lower will allow reducing the water vapor content at least 200 times from the initial level. A new universal system for collecting and drying of patient exhalation samples for a medical laser photo-acoustic gas analyzer has been developed and tested. A gas path for a medical laser gas analyzer has been designed, which allows sterilization of the internal gas path surfaces using ozone purging.

Exhaled air analysis as a potential fast method for early diagnosis of dengue disease

Dengue is a neglected tropical disease caused by arbovirus. Every year 390 million persons are infected with dengue, of which 96 million manifest clinically around the world, mainly in the Latin America, South-East Asia and Western Pacific. The disease manifests itself as a flu-like infection that generally is difficult to recognise from a normal flu or other viral infections. The mortality rate is around 20 % for the severe form of dengue, which readily could be decreased to below 1% with early, reliable diagnostic tools. Today there exist however no diagnostic tests for the early and rapid diagnosis of this disease. In this study, we report for the first time the possibility of identification of possible biomarkers associated with dengue disease in the exhaled air, and of the development of a breath test for fast, non-invasive and easy diagnosis of this disease. Further, we demonstrate a new deployable sensor technology based on a chemoresistive metal-ligand nanoassembly tailored for the identified possible biomarkers of dengue disease, which achieved 100 % accuracy for dengue diagnosis on our study group and can be used in both specialist and non-specialist settings. Nevertheless, as the present study was performed on a limited number of patients because of the difficulty to recruit a high number of patients because dengue is a neglected disease, future validation tests on a higher cohort are necessary for corroborating the results obtained in the present study.

Microelectronic Gas sensors for Non-invasive Analysis of Exhaled Gases

Interest in the research of small-sized gas sensors (especially semiconductor) for medical applications has sharply increased in recent years. Requirements for to such sensors are their high sensitivity, performance and stability to very low concentrations of gases, mainly exhaled by a living organism. Today the doctor not only polls, and examines the patient but also sends it to the lab-tests of blood, urine, perform an electrocardiogram, etc. But, for example, today’s periodic monitoring of glucose concentrations in the blood induces acute pain, risk of virus (e.g., hepatitis B) infection from needles, and other difficulties in frequent monitoring. Even in 1784, Antoine Lavoisier wrote that of all the phenomena of life, none is more striking and worthier for physicists and physiologists than phenomena accompanying the breath. Meanwhile, one of the most important directions of modern medicine is non-invasive diagnostics of the patient, based on the analysis of exhaled air in a special device.