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Essential oils are valuable in various industries, but their easy adulteration can cause adverse health effects. Electronic nasal sensors offer a solution for adulteration detection. This article proposes a new system for characterising essential oils based on low-cost sensor networks and machine learning techniques. The sensors used belong to the MQ family (MQ-2, MQ-3, MQ-4, MQ-5, MQ-6, MQ-7, and MQ-8). Six essential oils were used, including Cistus ladanifer, Pinus pinaster, and Cistus ladanifer oil adulterated with Pinus pinaster, Melaleuca alternifolia, tea tree, and red fruits. A total of up to 7100 measurements were included, with more than 118 h of measurements of 33 different parameters. These data were used to train and compare five machine learning algorithms: discriminant analysis, support vector machine, k-nearest neighbours, neural network, and naive Bayesian when the data were used individually or when hourly mean values were included. To evaluate the performance of the included machine learning algorithms, accuracy, precision, recall, and F1-score were considered. The study found that using k-nearest neighbours, accuracy, recall, F1-score, and precision values were 1, 0.99, 0.99, and 1, respectively. The accuracy reached 100% with k-nearest neighbours using only 2 parameters for averaged data or 15 parameters for individual data.

To evaluate the accuracy of a new electronic nose to recognize prostate cancer in urine samples.A blind, prospective study on consecutive patients was designed. Overall, 174 subjects were included in the study: 88 (50.6%) in prostate cancer group, and 86 (49.4%) in control group. Electronic nose performance for prostate cancer was assessed using sensitivity and specificity. The diagnostic accuracy of electronic nose was reported as area under the receiver operating characteristic curve.The electronic nose in the study population reached a sensitivity 85.2% (95% confidence interval 76.1-91.9; 13 false negatives out of 88), a specificity 79.1% (95% confidence interval 69.0-87.1; 18 false positives out of 86). The accuracy of the electronic nose represented as area under the receiver operating characteristic curve 0.821 (95% confidence interval 0.764-0.879).The diagnostic accuracy of electronic nose for recognizing prostate cancer in urine samples is high, promising and susceptible to supplemental improvement. Additionally, further studies will be necessary to design a clinical trial to validate electronic nose application in diagnostic prostate cancer nomograms.

[ES] Encontrar un método no invasivo de clasificación fiable para distinguir entre pacientes con cancer de próstata e hiperplasia benigna de próstata no es una tarea trivial. El antígeno prostático específico mas utilizado presenta un au- mento en otras situaciones como la retención de orina o la eyaculación. Los productos metabólicos celulares como los compuestos volatiles en forma de bio-fluidos presentan una oportunidad para estudiarlos con la tecnología de semiconductores de óxido de metal. Una nariz electrónica diseñada para estos biofiuidos podría convertirse en una prueba ambulatoria clave para disminuir el número de biopsias. El diseño 3D, la creación de circuitos electrónicos, neumáticos, la adecuación de las muestras, la creación de una base de datos estandarizada para narices electrónicas, la definición de una interfaz de usuario amigable para el profesional sanitario, un sistema securizado para la comunicación con un servidor de almacenamiento de datos y todo el software necesario para hacer viable la democratización de las narices electrónicas en atención hospitalaria configuran la estrategia del trabajo. Además, el método empleado para conseguir aumentar el número de datos ha resultado determinante para hacer mas sencillo el entrenamiento de la red neuronal con la que se ha logrado una precisión del 87% en la clasificación entre pacientes de cancer de próstata e hiperplasia benigna de próstata. Se ha escogido un formato libro donde recoger todos los aspectos significativos de la realización del estudio. El primer capítulo se centra en el proyecto de tesis a financiar, la problemática a resolver, los objetivos y el plan de trabajo. En el segundo capítulo se definen los conceptos, el sentido del olfato, la vejiga, la próstata, los sensores utilizados, indicadores de cancer y otros elementos como la nariz electrónica. Es con una nariz electrónica de donde se obtienen las señales que se tratan en el capítulo tercero. En este capítulo se muestran las características de las señales provenientes de pacientes con cancer de próstata y pacientes con hiperplasia benigna de próstata, su tratamiento, filtrado, comparación y uso para la clasificación de pacientes. Asimismo, se muestran dos métodos distintos de clasificación y estudio de los algoritmos para automatizar la misma. El capítulo cuarto se centra en la construcción de un prototipo. Se ha abordado este capítulo como un manual de construcción que permita al lector conocer el proceso realizado, la toma de decisiones y la técnica utilizada para la realización del hardware, software y el modelo 3D. Dado que la diversidad de especialidades que confluyen en el mismo proyecto puede imposibilitar el dominio de alguno de los campos tratados, incluso dentro del mismo campo de especialización, se ha preparado este capítulo con diagramas y código fu- ente que acompaña a las explicaciones de forma detallada. El propósito de este capítulo es permitir a investigadores de diversas areas de conocimiento su construcción sin necesidad de profundizar en otros campos. Además, en este capítulo se detallan los procedimientos a fin de favorecer la democratización de la nariz electrónica como instrumento científico y con la esperanza de proporcionar la base para futuras implementaciones en la comunidad científica. Para el autor, la tesis no es sólo un documento, es un período de evolución personal. Ha estado condicionada por factores diversos, una pandemia, el planteamiento inicial, la financiación, el grupo de acogida, la línea de investigación, el desarrollo socio-económico del autor y el propio autoaprendizaje en el proceso de ejecución. Es por ello que se ha plasmado en el capítulo quinto lo que ha guiado de una u otra manera, pero de forma significativa, la toma de decisiones. Este capítulo versa sobre el trabajo futuro y tres proyectos, COST y H2020, DE1-SoC ADC e-Nose y Detección de tumores, que han ejercido influencia en el desarrollo de la tesis. Las conclusiones se recogen en el capítulo sexto. No obstante, cada capítulo dispone de un apartado llamado "Reflexiones" donde se anotan aquellas ideas y conclusiones concretas sobre el mismo. De esta forma se proporciona al lector un instrumento de lectura rápida que permita su consulta como si se tratara de un manual, sin necesidad de leer la totalidad del documento. En resumen, en este estudio se detallan los métodos y procedimientos de la investigación realizada con pacientes de cáncer de próstata e hiperplasia benigna de próstata con el propósito de conseguir un prototipo de una nariz electrónica para la clasificación de pacientes haciendo uso de orina como biofluido. Se ha tratado de escribir una referencia desde la que seguir construyendo conocimiento en torno a las narices electrónicas aplicadas a la clasificación de pacientes., [CA] Trobar una mètode no invasiu de classificació fiable per a distingir entre pacients amb càncer de pròstata i hiperplàsia benigna de pròstata no és una tasca trivial. L'antigen prostàtic específic més utilitzat presenta un augment en altres situacions com la retenció d'orina o l'ejaculació. Els productes metabòlics cel·lulars com els compostos volàtils en forma de bio-fluids presenten una oportunitat per tal d'estudiar-los amb la tecnologia de semiconductors d'òxid de metall. Un nas electrònic dissenyat per a aquestos bio-fluids podria convertir-se en una prova ambulatòria clau per tal de disminuir el nombre de biòpsies. El disseny 3D, la creació de circuits electrònics, pneumàtics, l'adequació de les mostres, la creació d'una base de dades estandarditzada per a nassos electrònics, la definició d'una interfície d'usuari amigable per al professional sanitari, un sistema securitzat per a la comunicació amb un servidor d'emmagatzemament de dades i tot el software necessari per tal de fer viable la democratització dels nassos electrònics en atenció hospitalària configuren l'estratègia del treball. A més, el mètode emprat per a aconseguir augmentar el nombre de dades ha resultat determinant per fer més senzill l'entrenament de la xarxa neuronal amb la qual s'ha aconseguit una precisió del 87% a la classificació entre pacients de càncer de pròstata i hiperplàsia benigna de pròstata. S'ha escollit un format llibre on recollir tots els indrets significatius de la realització de l'estudi. El primer capítol es centra en el projecte de tesi a finançar, la problemàtica a resoldre, els objectius i el pla de treball. Al segon capítol es defineixen els conceptes, el sentit de l'olfacte, la bufeta, la próstata, els sensors utilitzats, indicadors de càncer i altres elements com el nas electrònic. És amb un nas electrònic d'on s'obtenen les senyals que es tracten al capítol tercer. En aquest capítol es mostren les característiques dels senyals provinents de pacients amb càncer de pròstata i pacients amb hiperplàsia benigna de próstata, el seu tractament, filtrat, comparació i ús per a la classificació de pacients. Així mateix, es mostren dos mètodes diferents de classificació i estudi dels algorismes per a automatitzar la mateixa. El capítol quart es centra en la construcció d'un prototip. S'ha abordat aquest capítol com un manual de construcció que permeta al lector conéixer el procés realitzat, la presa de decisions i la tècnica emprada pera la realització tant del hardware, els software i com el model 3D. Com que la diversitat d'especialitats que conflueixen en el mateix projecte pot impossibilitar el domini d'algun dels camps tractats, inclòs dins del mateix camp d'especialització, s'ha preparat aquest capítol amb diagrames i codi font que acompanya les explicacions de forma detallada. El propòsit d'aquest capítol és permetre a investigadors de diverses àrees de coneixement la seva construcció sense necessitat d'aprofundir en altres camps. A més, en aquest capítol es detallen els procediments per tal d'afavorir la democratització del nas electrònic com a instrument científic i amb la esperança de proporcionar la base per a futures implementacions en la comunitat científica. Per a l'autor, la tesi no és sols un document, és un període d'evolució personal. Ha estat condicionada per factors diversos, una pandèmia, el plantejament inicial, el finançament, el grup d'acollida, la línia d'investigació, el desenvolupament socio-econòmic de l'autor i el propi autoaprenentatge al procés d'execució. És per això que s'ha plasmat al capítol cinqué allò que ha guiat d'una manera o d'altra, però de forma significativa, la presa de decisions. Aquest capítol versa sobre el treball futur i tres projectes, COST i H2020, DE1-SoC ADC e-Nose i Detecció de tumors, que han exercit influència al desenvolupament de la tesi. És un exercici de reflexió al voltant dels mateixos i són una mostra de la capacitat investigadora de l'autor. Les conclusions es recullen al capítol sisé. No obstant això, cada capítol disposa d'un apartat anomenat "Reflexions" on s'anoten aquelles idees i conclusions concretes sobre el mateix. D'aquesta manera es proporciona al lector un instrument de lectura ràpida que permeta la seva consulta com si es tractés d'un manual, sense necessitat de llegir la totalitat del document. En resum, en aquest estudi es detallen els mètodes i procediments de la investigació realitzada amb pacients de càncer de pròstata i hiperplàsia benigna de pròstata amb el propòsit d'aconseguir un prototip d'un nas electrònic per a la classificació de pacients fent ús d'orina com a bio-fluid. S'ha tractat d'escriure una referència des d'on seguir construint coneixement al voltant dels nassos electrònics aplicats a la classificació de pacients., [EN] Finding a reliable non-invasive classification method to distinguish between patients with prostate cancer and benign prostatic hyperplasia is not a trivial task. The most commonly used specific prostate antigen shows an increase in other situations such as urinary retention or ejaculation. Cellular metabolic products, such as volatile compounds in the form of bio- fiuids, present an opportunity to study them by using metal oxide semiconduc- tor technology. An electronic nose designed for these bio-fiuids could become a key ambulatory test in order to decrease the number of biopsies. The strategy of the work is configured in diferent fields. Design a 3D set to enclose the electronics and penumatic circuits. The suitability of the samples it has to be studied furthermore the creation of a standardized database for electronic noses to store these samples. The definition of a friendly user interface for the health professional besides a system secured for communication with a data storage server. To sum up, all the software and hardware necessary to make viable the democratization of electronic noses in hospital care. In addition, the method be inployed to increase the number of data has been decisive to simplify the training of the neural network with which an accuracy of 87% has been achieved in the classification between prostate cancer patients and benign prostatic hyperplasia. A book format has been chosen to collect all the significant points of the study. The first chapter focuses on the thesis project to be financed, the problem to be solved, the objectives and the work plan. The second chapter defines the concepts, the sense of smell, the bladder, the prostate, the sensors used, cancer indicators and other elements such as the electronic nose. It is with an electronic nose that the signals discussed in chapter three are obtained. This chapter shows the characteristics of signals from patients with prostate cancer and patients with benign prostatic hyper- plasia, their treatment, filtering, comparison and use for patient classification. Likewise, two different methods of classification and study of the algorithms to automate the same are shown. The fourth chapter focuses on the construction of a prototype. This chapter has been approached as a construction manual that allows the reader to know the process carried out, the decision-making and the technique used to make both the hardware, the software and the 3D. Since the diversity of specialties that converge in the same project can make it impossible to master any of the fields discussed, including within the same field of specialization, this chapter has been prepared with diagrams and source code that accompanies the explanations of form detailed. The purpose of this chapter is to allow researchers from various areas of knowledge to construct it without the need to delve into other fields. In addition, this chapter details the procedures to promote the democratization of the electronic nose as a scientific instrument and with the hope of providing the basis for future implementations in the scientific community. For the author, the thesis is not just a document, it is a period of personal evolution. It has been conditioned by various factors, a pandemic, the initial approach, the funding, the host group, the line of research, the socioof the author and the self-learning in the execution process. That is why what has been shaped in the fifth has guided in one way or another, but in a significant way, the decision-making. This chapter deals with future work and three projects, COST and H2020, DE1-SoC ADC eNose and Tumor Detection, which have influenced the development of the thesis. It is an exercise in reflection about them and they are a sample of the author's research capacity. The conclusions are collected in chapter six. However, each chapter has a section called "Reflections" where those specific ideas and conclusions about the same are noted.

Mesothelioma is an aggressive tumor originating from the mesothelial cells of the pleural or peritoneal cavity. This thesis focuses on the treatment of pleural mesothelioma. For long, chemotherapy has been the standard of care, leading to an overall survival of about 15 months. In this thesis, a phase 2 trial is performed using two checkpoint inhibitors, nivolumab (anti-PD-1) plus ipilimumab (anti-CTLA-4), to treat recurrent mesothelioma after at least one line of chemotherapy. Of the 34 patients evaluable for response 29% had a partial response and 38% patients had stable disease, so 68% of patients achieved disease control, the primary endpoint. These results exceeded expectations and rejected the alternative hypothesis. In part III translational research was performed on blood samples, pleural biopsies and breath analyses at baseline and after 6 weeks of treatment. In order to find markers of response and try to explain how immunotherapy affects the tumor microenvironment and immune cell subsets of the peripheral blood.

The use of electronic noses (eNoses) as analysis tools are growing in popularity; however, the lack of a comprehensive, visual representation of how the different classes are organized and distributed largely complicates the interpretation of the classification results, thus reducing their practicality. The new contributions of this paper are the assessment of the multivariate classification performance of a custom, low-cost eNose composed of 16 single-type (identical) MOX gas sensors for the classification of three volatiles, along with a proposal to improve the visual interpretation of the classification results by means of generating a detailed 2D class-map representation based on the inverse of the orthogonal linear transformation obtained from a PCA and LDA analysis. The results showed that this single-type eNose implementation was able to perform multivariate classification, while the class-map visualization summarized the learned features and how these features may affect the performance of the classification, simplifying the interpretation and understanding of the eNose results.

BACKGROUND: Electronic noses (eNoses) are emerging point-of-care tools that may help in the subphenotyping of chronic respiratory diseases such as asthma.OBJECTIVE: We aimed to investigate whether eNoses can classify atopy in pediatric and adult patients with asthma.METHODS: Participants with asthma and/or wheezing from 4 independent cohorts were included; BreathCloud participants (n = 429), Unbiased Biomarkers in Prediction of Respiratory Disease Outcomes adults (n = 96), Unbiased Biomarkers in Prediction of Respiratory Disease Outcomes pediatric participants (n = 100), and Pharmacogenetics of Asthma Medication in Children: Medication with Anti-Inflammatory Effects 2 participants (n = 30). Atopy was defined as a positive skin prick test result (≥3 mm) and/or a positive specific IgE level (≥0.35 kU/L) for common allergens. Exhaled breath profiles were measured by using either an integrated eNose platform or the SpiroNose. Data were divided into 2 training and 2 validation sets according to the technology used. Supervised data analysis involved the use of 3 different machine learning algorithms to classify patients with atopic versus nonatopic asthma with reporting of areas under the receiver operating characteristic curves as a measure of model performance. In addition, an unsupervised approach was performed by using a bayesian network to reveal data-driven relationships between eNose volatile organic compound profiles and asthma characteristics.RESULTS: Breath profiles of 655 participants (n = 601 adults and school-aged children with asthma and 54 preschool children with wheezing [68.2% of whom were atopic]) were included in this study. Machine learning models utilizing volatile organic compound profiles discriminated between atopic and nonatopic participants with areas under the receiver operating characteristic curves of at least 0.84 and 0.72 in the training and validation sets, respectively. The unsupervised approach revealed that breath profiles classifying atopy are not confounded by other patient characteristics.CONCLUSION: eNoses accurately detect atopy in individuals with asthma and wheezing in cohorts with different age groups and could be used in asthma phenotyping.

The artificial replication of an olfactory system is currently an open problem. The development of a portable and low-cost artificial olfactory system, also called electronic nose or eNose, is usually based on the use of an array of different gas sensors types, sensitive to different target gases. Low-cost Metal-Oxide semiconductor (MOX) gas sensors are widely used in such arrays. MOX sensors are based on a thin layer of silicon oxide with embedded heaters that can operate at different temperature set points, which usually have the disadvantages of different volatile sensitivity in each individual sensor unit and also different crossed sensitivity to different volatiles (unspecificity). This paper presents and eNose composed by an array of 16 low-cost BME680 digital miniature sensors embedding a miniature MOX gas sensor proposed to unspecifically evaluate air quality. In this paper, the inherent variability and unspecificity that must be expected from the 16 embedded MOX gas sensors, combined with signal processing, are exploited to classify two target volatiles: ethanol and acetone. The proposed eNose reads the resistance of the sensing layer of the 16 embedded MOX gas sensors, applies PCA for dimensional reduction and k-NN for classification. The validation results have shown an instantaneous classification success higher than 94% two days after the calibration and higher than 70% two weeks after, so the majority classification of a sequence of measures has been always successful in laboratory conditions. These first validation results and the low-power consumption of the eNose (0.9 W) enables its future improvement and its use in portable and battery-operated applications.

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System “eNose” is developed within a project “eNose for Internet of things”, which is a part of a project contest “Research Grant of Rezekne Acadaemy of Technologies”. The aim of this work is to explore whether it is possible to detect spoiled food with help of sensors and a neural network. System “eNose” is intended to detect and classify spoiled food products within storages and notify related users. Detection and classification are performed by four gas sensors and a neural network. As a result, a web application was developed that performs such functions as storage and sensor registration, neural network training, spoiled food detection based on sensor data, and user permission control. It was concluded that sensors for this application must be very precise in order to receive best possible results.

Дослідження складу ґрунтового повітря є надзвичайно важливою задачею, оскільки вміст компонентів газової фази ґрунту, зокрема СО2 та О2, безпосереднім чином відображає показники родючості ґрунту. В роботі проведено огляд щодо компонентного складу ґрунтового повітря, розглянуто існуючі методи визначення дихання ґрунту та показано перспективність використання сенсорного методу, який базується на використанні масиву датчиків, з можливістю проведення онлайн моніторингу без використання реагентів. З метою визначення чутливості синтезованих зразків відносно СО2 методом паро-газового транспорту синтезовано одновимірні наноструктури стануму (IV) оксиду та проведено їх модифікацію ітрієм для використання в чутливих шарах газових сенсорів. Досліджено вольт-амперні характеристики чистих та модифікованих наноструктур SnO2 на повітрі та в атмосфері карбон (IV) оксиду. Investigation of soil air composition is an extremely important task because the content of soil gas phase components, in particular CO2, O2 and NOx , directly reflects soil fertility. The composition of soil air, the so-called "breath of the earth", plays an important role in the nutrition of plants and is an indicator of biochemical and biological processes that occur in the soil. The study of soil gas regime is extremely important for agrochemical and microbiological studies and is a set of all related phenomena: the flow of gases into the soil and their movement along the soil profile; changes in the content and composition of gases in the ground air as a result of the absorption or release of individual gases in biological and biochemical processes, the exchange between soil and atmosphere, solid and liquid phases. Carbon dioxide and oxygen are the most dynamic gases among all gases of ground air. The growth of plants depends on the concentration of CO2, and when it reaches its optimal concentration it is possible to accelerate the growth of the crop. Oxygen of ground air is essential for soil fertility and especially necessary for microbiological processes. It actively participates in chemical reactions of mineral and organic substances and is actively absorbed by the roots of plants and microbes in the process of their breathing. This paper reviews the composition of ground air, considers existing methods of soil breathing determination and shows the prospect of sensor method with online monitoring without reagents usage. In order to determine the sensitivity of synthesized samples towards CO2, one-dimensional nanostructures of the tin (IV) oxide have been synthesized by vapor transport method and their modification by yttrium for use in sensitive layers of gas sensor has been done. The current-voltage characteristics of pure and modified SnO2 nanostructures at ambient and in the atmosphere of carbon (IV) oxide have been investigated. It is shown that yttrium modified onedimensional SnO2 nanostructures have a higher sensory response to carbon dioxide in comparison with the pure tin (IV) oxide sample, that is, they are much more promising for use in sensing systems of soil air composition study

The photoinitiated thiol−ene addition reaction is a highly stereo‐ and regioselective, and environmentally friendly reaction proceeding under mild conditions, hence it is ideally suited for the synthesis of carbohydrate mimetics. A comprehensive study on UV‐light‐induced reactions of 2,3‐unsaturated O‐, C‐, S‐ and N‐glycosides with various thiols was performed. The effect of experimental parameters and structural variations of the alkenes and thiols on the efficacy and regio‐ and stereoselectivity of the reactions was systematically studied and optimized. The type of anomeric heteroatom was found to profoundly affect the reactivity of 2,3‐unsaturated sugars in the thiol−ene couplings. Hydrothiolation of 2,3‐dideoxy O‐glycosyl enosides efficiently produced the axially C2‐S‐substituted addition products with high to complete regioselectivity. Moderate efficacy and varying regio‐ and stereoselectivity were observed with 2,3‐unsaturated N‐glycosides and no addition occurred onto the endocyclic double bond of C‐glycosides. Upon hydrothiolation of 2,3‐unsaturated S‐glycosides, the addition of thiyl radicals was followed by elimination of the thiyl aglycone resulting in 3‐S‐substituted glycals., A comprehensive study on radical‐mediated hydrothiolation of 2,3‐unsaturated O‐, C‐, S‐ and N‐glycosides with a broad range of thiols was performed to gain a deeper insight into how experimental parameters and structural variations of the alkenes and thiols influence the efficacy and regio‐ and stereoselectivity of the reactions.

This paper assesses a custom single-type electronic nose (eNose) applied to differentiate the complex aromas generated by the caffeinated and decaffeinated versions of one encapsulated espresso coffee mixture type. The eNose used is composed of 16 single-type (identical) metal–oxide semiconductor (MOX) gas sensors based on microelectromechanical system (MEMS). This eNose proposal takes advantage of the small but inherent sensing variability of MOX gas sensors in order to provide a multisensorial description of volatiles or aromas. Results have shown that the information provided with this eNose processed using LDA is able to successfully discriminate the complex aromas of one caffeinated and decaffeinated encapsulated espresso coffee type.

Asthma is a chronic respiratory disease that can lead to exacerbations, defined as acute episodes of worsening respiratory symptoms and lung function. Predicting the occurrence of these exacerbations is an important goal in asthma management. The measurement of exhaled breath by electronic nose (eNose) may allow for the monitoring of clinically unstable asthma and exacerbations. However, data on its ability to perform this is lacking. We aimed to evaluate whether eNose could identify patients that recently had asthma exacerbations. We performed a cross-sectional study, measuring exhaled breath using the SpiroNose in adults with a physician-reported diagnosis of asthma. Patients were randomly divided into a training (n = 252) and validation (n = 109) set. For the analysis of eNose signals, principal component (PC) and linear discriminant analysis (LDA) were performed. LDA, based on PC1-4, reliably discriminated between patients who had a recent exacerbation from those who had not (training receiver operating characteristic (ROC)–area under the curve (AUC) = 0.76,95% CI 0.69–0.82), (validation AUC = 0.76, 95% CI 0.64–0.87). Our study showed that, exhaled breath analysis using eNose could accurately identify asthma patients who recently had an exacerbation, and could indicate that asthma exacerbations have a specific exhaled breath pattern detectable by eNose.

This work presents a H2S selective resistive gas sensor design based on a chemical field effect transistor (ChemFET) with open gate formed by hundreds of high temperature chemical vapour deposition (CVD) grown zinc oxide nanowires (ZnO NW). The sensing ability of pristine ZnO NWs and surface functionalized ZnO NWs for H2S is analysed systematically. ZnO NWs are functionalized by deposition of discontinuous gold (Au) nanoparticle films of different thicknesses of catalyst layer ranging from 1 to 10 nm and are compared in their gas sensing properties. All experiments were performed in a temperature stabilized small volume compartment with adjustable gas mixture at room temperature. The results allow for a well-founded understanding of signal-to-noise ratio, enhanced response, and improved limit of detection due to the Au functionalisation. Comprehension and controlled application of the beneficial effects of Au catalyst on ZnO NWs allow for the detection of very low H2S concentrations down to 10 ppb, and a theoretically estimated 500 ppt in synthetic air at room temperature., publishedVersion

Unsere Atemluft ist t��glichen Schwankungen ausgesetzt und die Marktnachfrage nach Sensoren, die die Luftqualit��t messen k��nnen, steigt rapide an. Ein gro��er Teil dieser Nachfrage kann mit Metall-Oxid Gas Sensoren bedient werden. Diese Art von Gassensoren hat jedoch einige Nachteile im Bezug auf Genauigkeit, Langzeitstabilit��t, Leistungsaufnahme und Selektivit��t. Auch fehlen gro��volumige Anwendungsbeispiele auf dem Markt, die Metall-Oxid (MOX) Gassensoren einsetzen und dabei alle Systemanforderungen erf��llen. Diese Arbeit stellt die neueste Entwicklung der "KArlsruhe MIkro NAse", einer im Rahmen der EU Horizon 2020 Initiative namens SMOKESENSE entwickelten elektrischen Nase, vor und vergleicht diese mit dem aktuellen Stand der Technik f��r Metalloxid-Gassensoren. Es wird gezeigt, dass durch UV-Anregung der $SnO_{2}$-Nanodr��hte ein geringerer Stromverbrauch sowie eine minimierte Siloxan-Kontaminierung im Vergleich zu klassischen MOX-Sensoren erzielt wird. Zudem l��sst sich mittels Aerosol-Jet-Druck eine vereinfachte und kosteng��nstigere Herstellung der Sensoren realisieren. Um die Massenproduktionstauglichkeit f��r eine Anwendung als intelligenter Feuersensor sicherzustellen, wird der Wachstumsprozess der Nanodr��hte optimiert. Au��erdem wird ein neuartiges chemisches FET-��hnliches Sensorkonzept namens Chem-FET vorgestellt, das im Vergleich zu UV-KAMINA ein verbessertes Signal-Rausch-Verh��ltnis und eine schnellere Reaktionszeit bietet. Eine ��berwachte Lernmethode des Maschinellen Lernens basierend auf einer linearen Diskriminanzfunktion wird verwendet, um verschiedene Zielger��che zu klassifizieren. In einer Anwendung als Feuersensor erwiesen sich die entwickelten Sensorprototypen als konkurrenzf��hig. Zus��tzlich werden M��glichkeiten aufgezeigt, das Sensorprinzip als Plattform f��r andere Anwendungsarten verwenden zu k��nnen. W��hrend mit den vorgestellten Methoden die Leistung des Gesamtsystems optimiert werden konne, bleibt als Ausblick Verbesserungsbedarf in Bereichen, wie z. B. der Charakterisierung von Ger��chen und der Testmethodik f��r die Anwendung in hohen St��ckzahlen.

Breath analysis using eNose technology can be used to discriminate between asthma and COPD patients, but it remains unclear whether results are influenced by smoking status. We aim to study whether eNose can discriminate between ever- vs. never-smokers and smoking &lt, 24 vs. &gt, 24 h before the exhaled breath, and if smoking can be considered a confounder that influences eNose results. We performed a cross-sectional analysis in adults with asthma or chronic obstructive pulmonary disease (COPD), and healthy controls. Ever-smokers were defined as patients with current or past smoking habits. eNose measurements were performed by using the SpiroNose. The principal component (PC) described the eNose signals, and linear discriminant analysis determined if PCs classified ever-smokers vs. never-smokers and smoking &lt, 24 h. The area under the receiver–operator characteristic curve (AUC) assessed the accuracy of the models. We selected 593 ever-smokers (167 smoked &lt, 24 h before measurement) and 303 never-smokers and measured the exhaled breath profiles of discriminated ever- and never-smokers (AUC: 0.74, 95% CI: 0.66–0.81), and no cigarette consumption &lt, 24h (AUC 0.54, 95% CI: 0.43–0.65). In healthy controls, the eNose did not discriminate between ever or never-smokers (AUC 0.54, 95% CI: 0.49–0.60) and recent cigarette consumption (AUC 0.60, 95% CI: 0.50–0.69). The eNose could distinguish between ever and never-smokers in asthma and COPD patients, but not recent smokers. Recent smoking is not a confounding factor of eNose breath profiles.

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

In this work, we investigate the catalytic effects of gold (Au) and platinum (Pt) nanoparticle layer deposition on highly sensitive zinc oxide (ZnO) nanowires (NWs) used for selective H2S detection in the sub-ppm region. Optimum quality pristine ZnO NWs were grown by high temperature chemical vapor deposition (CVD) in the vapor liquid solid growth (VLS) mode on silicon with a thin Au layer acting as a growth catalyst. The surface of pristine ZnO NWs was modified by systematic magnetron sputtering of discontinuous Au and Pt layers of 0���5 nm thickness. Resistive gas sensors based on the gas sensing mechanism of a chemical field effect transistor (ChemFET) with open gate, which is formed by hundreds of parallel aligned pristine Aumodified or Pt-modified ZnO NWs, were measured toward H2S diluted in dry nitrogen (N2) or in dry synthetic air at room temperature. Gas sensing results showed a largely improved response due to the catalytic effects of metal deposition on the ZnO NW surface. Controlled application of ZnO NW growth under optimized conditions and metal catalyst deposition showed a clear response enhancement toward 1 ppm H2S from the initial 20% achieved with pristine ZnO to over 5000% with ZnO NWs covered by 5 nm of Au, and, hence, significantly lower than the limit of detection., publishedVersion

Aim: Rapid identification of bacteria would facilitate timely initiation of therapy and improve cost–effectiveness of treatment. Traditional methods (culture, PCR) require reagents, consumables and hours to days to complete the identification. In this study, we examined whether differential mobility spectrometry could classify most common bacterial species, genera and between Gram status within minutes. Materials & methods: Cultured bacterial sample gaseous headspaces were measured with differential mobility spectrometry and data analyzed using k-nearest-neighbor and leave-one-out cross-validation. Results: Differential mobility spectrometry achieved a correct classification rate 70.7% for all bacterial species. For bacterial genera, the rate was 77.6% and between Gram status, 89.1%. Conclusion: Largest difficulties arose in distinguishing bacteria of the same genus. Future improvement of the sensor characteristics may improve the classification accuracy.

Thioglycosides and C‐glycosides represent pharmacologically useful classes of glycomimetics that possess a high degree of biological stability. One emerging tool for the stereoselective synthesis of thioglycosides is the photoinitiated addition of thiols to unsaturated sugars. Moreover, thiyl radical‐mediated reactions of exo‐glycals and 1‐substituted endo‐glycals offer facile routes to β‐C‐glycosidic structures. This Concept article summarizes the thiol‐ene coupling strategies developed recently by our group and Somsák's group for the synthesis of several kinds of glycomimetics which are difficult to synthesize by conventional methods. One unusual characteristic of the thiol‐ene reactions of endo‐glycals is that heating inhibits, whereas cooling promotes the reaction. This unique temperature dependence as well as the effects of the enose structures and thiol configurations on the efficacy and stereoselectivity of the reactions are also discussed., UV‐light induced radical‐mediated addition of thiols onto endo‐ or exo‐cyclic double bonds of unsaturated sugars offers an easy and stereoselective route to a broad range of stable glycomimetics including 1,2‐cis‐α‐S‐glycosides and new types of β‐C‐glycosides.

Background: Cyclosporine A (CsA) is an immunosuppressant with therapeutic indications in various immunological diseases; however, its use is associated with chronic nephropathy. Oxidative stress has a crucial role in CsA-induced nephrotoxicity. The present study evaluates the protective effect of edaravone on CsA-induced chronic nephropathy and investigates its antioxidant and nitric oxide modulating property. Methods: Male Sprague-Dawley rats (n=66) were distributed into nine groups, including a control (group 1) (n=7). Eight groups received CsA (15 mg/kg) for 28 days while being treated. The groups were categorized as: • Group 2: Vehicle (n=10) • Groups 3, 4, and 5: Edaravone (1, 5, and 10 mg/kg) (n=7 each) • Group 6: Diphenyliodonium chloride, a specific endothelial nitric oxide synthase (eNOS) inhibitor (n=7) • Group 7: Aminoguanidine, a specific inducible nitric oxide synthase (iNOS) inhibitor (n=7) • Group 8: Edaravone (10 mg/kg) plus diphenyliodonium chloride (n=7) • Group 9: Edaravone (10 mg/kg) plus aminoguanidine (n=7) Blood urea nitrogen and serum creatinine levels, malondialdehyde, superoxide dismutase, and glutathione reductase enzyme activities were measured using standard kits. Renal histopathological evaluations and measurements of eNOS and iNOS gene expressions by RT-PCR were also performed. Data were analyzed using one-way analysis of variance (ANOVA) followed by Tukey’s test (SPSS software version 18.0). Results: Edaravone (10 mg/kg) significantly attenuated CsA-induced oxidative stress, renal dysfunction, and kidney tissue injury. Aminoguanidine improved the renoprotective effect of edaravone. Edaravone reduced the elevated mRNA level of iNOS, but could not alter the level of eNOS mRNA significantly. Conclusion: Edaravone protects against CsA-induced chronic nephropathy using antioxidant property and probably through inhibiting iNOS gene expression.

Die idiopathische pulmonale Fibrose (IPF) ist eine schwere chronisch progrediente Lungenerkrankung mit einer mittleren Überlebenszeit von 3 bis 5 Jahren ab dem Zeitpunkt der Erstdiagnose. Das Bronchialkarzinom gehört zu den häufigsten malignomassoziierten Todesursachen weltweit sowohl bei Frauen als auch bei Männern. Beide Erkrankungen haben gemeinsam, dass eine frühestmögliche Diagnosestellung die Prognose deutlich positiv beeinflussen kann, jedoch häufig die Diagnosestellung erst spät erfolgt, da es bisher keine zuverlässigen Screening-Möglichkeiten gibt.In dieser Arbeit kam die Technologie der elektronischen Nase zur Anwendung, ein sich in den letzten Jahrzehnten rasch entwickelndes Feld der nicht-invasiven Diagnostik. Ziel der Arbeit war es im Rahmen einer Studie mit dem Gerät Aeonose® 174 Patienten mit interstitieller Lungenerkrankung und 120 Patienten mit einem Bronchialkarzinom sowie 33 Gesunden und 23 COPD-Patienten zu untersuchen und herauszuarbeiten, ob die Aeonose® in der Lage ist, die erkrankten Patienten mit hoher Spezifität und Sensitivität von gesunden Kontrollpersonen zu unterscheiden. Zudem wurde gefragt, ob die Aeonose® darüber hinaus die Erkrankungen in Querschnittsanalysen voneinander unterscheiden kann.Der in dieser Studie entwickelte Algorithmus zur Differenzierung von Bronchialkarzinom-Patienten bzw. Patienten mit interstitiellen Lungenerkrankungen von der Kontrollgruppe erbrachte Ergebnisse mit guter Sensitivität und Spezifität bei einem Fall-Kontroll-Ansatz. Jedoch scheiterte die Aeonose® größtenteils bei der sicheren Identifizierung der COPD-Kohorte und der Bronchialkarzinom-Kohorten in partieller oder kompletter Remission als Karzinom-frei im Blindversuch. Unsere Daten legen nahe, dass basierend auf der Vorgehensweise immer nur zwei Konditionen in der Trainingsphase miteinander zu vergleichen relevante VOC-Signale, die von Komorbiditäten wie der COPD herrührten, fälschlicherweise zur Unterscheidung von gesunden und kranken Personen geführt haben. Trotz dieser etwas unzufriedenstellenden Ergebnisse ist weiterhin davon auszugehen, dass VOC-Signaturen, wenn sie adäquat gebündelt und dem vorliegenden pulmonalen Phänotyp zugeordnet wären, für die rasche und frühe Erkennung von Bronchialkarzinomen und interstitiellen Lungenerkrankungen genutzt werden und Screeningprogramme für Bronchialkarzinome, die auf low dose CT basieren, vervollständigen könnten. Studien mit einem weitaus größeren Datensatz an Patienten, welche auf Analysen durch künstliche Intelligenzen oder Hauptkomponentenanalysen (principle compound analysis) basieren, könnten weitaus besser in der Lage sein diese Geräte zu trainieren und schlussendlich die sichere Differenzierung innerhalb der interstitiellen Lungenerkrankungen sowie von Malignomen und Nicht-Malignomen ermöglichen., The idiopathic pulmonary fibrosis (IPF) is a progressive lung disease with a poor mean survival rate of about 3 - 5 years after definite diagnosis. Lung cancer accounts for more deaths than any other cancer in both men and women. Both diseases, IPF and lung cancer, have in common that an early diagnosis can have massive positive impact on the prognosis. Nevertheless, the definite diagnoses in most cases are delayed to a late stage of the disease, as there are no uncomplicated valid screening programs yet.This study investigates the electronic nose technology, which has been of great scientific interest over the last few years and is a rapidly emerging field of medical diagnostics. In this study, we used a device called Aeonose® by the dutch company The eNose company.174 patients with ILD and 91 lung cancer patients were measured by Aeonose®. Aim of this study was to investigate whether the Aeonose® is able to distinguish the diseased patients from healthy controls with a high sensitivity and specifcity and furthermore to study if the Aeonose® could distinguish the diseases in cross-sectional analyses.The algorithm developed in this study to separate LC from controls using the Aeonose® resulted in good sensitivity and specificity in separating these two conditions in a case-control approach, but largely failed to safely identify cohorts of COPD and LC in partial or complete remission as being cancer-free in a blinded approach. The Aeonose® also showed potential in distinguishing ILD from HC in direct comparison. Our data suggest that - based on the herein applied approach of dichotomous comparison of conditions for training - relevant VOC signals originating from comorbidities such as COPD may have erroneously led to separation between LC or ILD and healthy control. Notwithstanding these somewhat disappointing results, we nevertheless believe that VOC signatures, once being adequately clustered and annotated to the underlying pulmonary phenotype, may be used for rapid and safe detection of lung cancer and ILDs and to accomplish lung cancer screening programs based on low dose CT. We suggest that artificial intelligence or principle compound analysis - based studies of a much broader data set of patients with interstitial lung diseases may be much better suitable to train these devices and ultimately to allow safe differentiation within ILDs as well as cancer and non cancer.

Diseases of prematurity such as neonatal infections and bronchopulmonary dysplasia (BPD) are frequent in preterm neonates, resulting from incomplete organ development. Early and late onset neonatal infections are a primary reason for mortality in preterms during the neonatal period. BPD is caused by an inflammatory process that prevents further development of the premature lung, resulting in a chronic pulmonary disease with prolonged need for supplementary oxygen. Early prediction markers for BPD are still lacking. Likewise, valid diagnosis of invasive infection in preterm and term neonates is difficult due to unspecific clinical symptoms. In this project BPD and neonatal infections were investigated by analysing tracheal aspirates of 33 preterm and term neonates, which were collected during routine suctioning of the intubated patients. IL-6 and IFN-γ cytokine concentrations in the tracheal aspirates were measured by immunoassay. Conventional microbiological analysis consisting of gram staining, microscopy and bacterial culture was performed, as well as molecular analysis, which included PCR of 16S-rDNA and separation of the PCR- products by chromatography. Additionally, an electronic nose, a device that senses volatile organic compounds (VOCs) through 32 biopolymer sensors, was utilized. Smellprints were generated according to the detected VOCs. Preterms born before completion of 32 weeks that developed BPD later on did not show higher levels of IL-6 and IFN-γ in their tracheal aspirates when compared to preterms that did not develop BPD. Tracheal aspirate cytokines were also not elevated in patients with signs of systemic infection or detection of bacteria in the tracheal aspirate. Comparison of the different microbiological detection methods showed a high rate of mismatches. In patients that developed BPD, germs were detected significantly more often in the tracheal aspirate when compared to patients that did not develope BPD. The smellprint linear discriminant analysis showed promising results: smellprints from tracheal aspirates of patients with and without subsequent development of BPD differed significantly. Furthermore, smellprints from tracheal aspirates of neonates with laboratory-confirmed bloodstream infection differed significantly from those without infection, regardless of a positive or negative microbiological test result. The application of an electronic nose may prove useful in the prediction of BPD development and diagnosis of neonatal infections. Larger numbers of samples will be needed for further validation of the respective smellprint patterns., Eine Frühgeburt birgt aufgrund der Unreife der Organsysteme des Neugeborenen erhöhte Krankheitsrisiken. Dazu zählen unter anderem Infektionserkrankungen und die Bronchopulmonale Dysplasie (BPD). Early- oder Late-Onset Infektionen durch diverse Erreger sind bei Frühgeborenen eine der Hauptursachen für die Mortalität in der Neonatalperiode. Bei der BPD führen inflammatorische Prozesse in der unreifen Lunge zu einer chronischen Lungenschädigung mit persistierendem Sauerstoffbedarf im Verlauf. Hierfür fehlen valide Frühvorhersagemodelle. Auch was Infektionserkrankungen betrifft, ergeben sich bei Früh- und Neugeborenen wegen der unspezifischen Symptomatik diagnostische Schwierigkeiten. Im Hinblick auf die Prädiktion der BPD und die Diagnostik von systemischen Infektionen erfolgten in der vorliegenden Arbeit Untersuchungen am Trachealaspirat von 33 intubierten Früh- und Reifgeborenen. Das Trachealaspirat wurde beim routinemäßigen Absaugen der Patienten gewonnen. Die Konzentrationen der Zytokine IL-6 und IFN-γ im Trachealaspirat wurden mittels Immunassay bestimmt. Zudem wurden die Trachealaspiratproben mit zwei verschiedenen mikrobiologischen Untersuchungsverfahren auf das Vorhandensein von Bakterien untersucht: Der konventionelle Untersuchungsansatz umfasste Färbung und Mikroskopie sowie kulturelle Anzucht, der molekulare Ansatz bestand aus einer PCR der im Trachealaspirat vorhandenen 16S-rDNA sowie chromatographischer Auftrennung und Sequenzierung der Amplifikate. Des Weiteren kam eine Elektronische Nase zum Einsatz, ein tragbares Gerät, das volatile organische Substanzen (VOCs) detektiert. So wurde ein Smellprint, also ein Profil der emittierten Substanzen, für jede Trachealaspiratprobe – ähnlich einem individuellen Fingerabdruck – erstellt. Die Untersuchung zeigte keine signifikanten Unterschiede der Konzentrationen der Zytokine IL-6 und IFN-γ im Trachealaspirat von Frühgeborenen mit einem Gestationsalter < 32 SSW, die später eine BPD entwickelten und denen, die keine BPD entwickelten. Die Zytokinkonzentrationen im Trachealsekret korrelierten ebenfalls nicht mit dem Vorliegen einer systemischen Infektion oder dem Bakteriennachweis im Trachealaspirat. Der Vergleich des konventionellen und genomischen Erregernachweises im Trachealaspirat zeigte eine erhebliche Diskrepanz. Bei Patienten, die später eine BPD entwickelten, zeigten sich signifikant häufiger Bakterien im Trachealaspirat. Die erstmalig bei Neugeborenen durchgeführte Analyse der durch die Elektronische Nase erstellten Smellprints erbrachte erfolgversprechende Ergebnisse: Die Smellprints der Trachealaspirate von Frühgeborenen, die später eine BPD entwickelten und Frühgeborenen, die keine BPD entwickelten, unterschieden sich in der Diskriminanzanalyse signifikant. Ebenso unterschieden sich die Smellprints von Patienten mit einer laborchemisch bestätigten Infektion signifikant von Patienten ohne Infektionsparameter, unabhängig davon, ob Letztere einen positiven Keimnachweis im Trachealaspirat hatten oder nicht. Der Einsatz der Elektronischen Nase in der Neugeborenenmedizin ist also vielversprechend hinsichtlich der Prädiktion der BPD sowie der Diagnostik von systemischen Infektionen. Es sind jedoch weitere Studien zur Validierung dieser Methode notwendig.

Die idiopathische pulmonale Fibrose (IPF) ist eine schwere chronisch progrediente Lungenerkrankung mit einer mittleren Überlebenszeit von 3 bis 5 Jahren ab dem Zeitpunkt der Erstdiagnose. Das Bronchialkarzinom gehört zu den häufigsten malignomassoziierten Todesursachen weltweit sowohl bei Frauen als auch bei Männern. Beide Erkrankungen haben gemeinsam, dass eine frühestmögliche Diagnosestellung die Prognose deutlich positiv beeinflussen kann, jedoch häufig die Diagnosestellung erst spät erfolgt, da es bisher keine zuverlässigen Screening-Möglichkeiten gibt. In dieser Arbeit kam die Technologie der elektronischen Nase zur Anwendung, ein sich in den letzten Jahrzehnten rasch entwickelndes Feld der nicht-invasiven Diagnostik. Ziel der Arbeit war es im Rahmen einer Studie mit dem Gerät Aeonose® 174 Patienten mit interstitieller Lungenerkrankung und 120 Patienten mit einem Bronchialkarzinom sowie 33 Gesunden und 23 COPD-Patienten zu untersuchen und herauszuarbeiten, ob die Aeonose® in der Lage ist, die erkrankten Patienten mit hoher Spezifität und Sensitivität von gesunden Kontrollpersonen zu unterscheiden. Zudem wurde gefragt, ob die Aeonose® darüber hinaus die Erkrankungen in Querschnittsanalysen voneinander unterscheiden kann. Der in dieser Studie entwickelte Algorithmus zur Differenzierung von Bronchialkarzinom-Patienten bzw. Patienten mit interstitiellen Lungenerkrankungen von der Kontrollgruppe erbrachte Ergebnisse mit guter Sensitivität und Spezifität bei einem Fall-Kontroll-Ansatz. Jedoch scheiterte die Aeonose® größtenteils bei der sicheren Identifizierung der COPD-Kohorte und der Bronchialkarzinom-Kohorten in partieller oder kompletter Remission als Karzinom-frei im Blindversuch. Unsere Daten legen nahe, dass – basierend auf der Vorgehensweise immer nur zwei Konditionen in der Trainingsphase miteinander zu vergleichen – relevante VOC-Signale, die von Komorbiditäten wie der COPD herrührten, fälschlicherweise zur Unterscheidung von gesunden und kranken Personen geführt haben. Trotz dieser etwas unzufriedenstellenden Ergebnisse ist weiterhin davon auszugehen, dass VOC-Signaturen, wenn sie adäquat gebündelt und dem vorliegenden pulmonalen Phänotyp zugeordnet wären, für die rasche und frühe Erkennung von Bronchialkarzinomen und interstitiellen Lungenerkrankungen genutzt werden und Screeningprogramme für Bronchialkarzinome, die auf low dose CT basieren, vervollständigen könnten. Studien mit einem weitaus größeren Datensatz an Patienten, welche auf Analysen durch künstliche Intelligenzen oder Hauptkomponentenanalysen (principle compound analysis) basieren, könnten weitaus besser in der Lage sein diese Geräte zu trainieren und schlussendlich die sichere Differenzierung innerhalb der interstitiellen Lungenerkrankungen sowie von Malignomen und Nicht-Malignomen ermöglichen. The idiopathic pulmonary fibrosis (IPF) is a progressive lung disease with a poor mean survival rate of about 3 - 5 years after definite diagnosis. Lung cancer accounts for more deaths than any other cancer in both men and women. Both diseases, IPF and lung cancer, have in common that an early diagnosis can have massive positive impact on the prognosis. Nevertheless, the definite diagnoses in most cases are delayed to a late stage of the disease, as there are no uncomplicated valid screening programs yet. This study investigates the electronic nose technology, which has been of great scientific interest over the last few years and is a rapidly emerging field of medical diagnostics. In this study, we used a device called Aeonose® by the dutch company The eNose company. 174 patients with ILD and 91 lung cancer patients were measured by Aeonose®. Aim of this study was to investigate whether the Aeonose® is able to distinguish the diseased patients from healthy controls with a high sensitivity and specifcity and furthermore to study if the Aeonose® could distinguish the diseases in cross-sectional analyses. The algorithm developed in this study to separate LC from controls using the Aeonose® resulted in good sensitivity and specificity in separating these two conditions in a case-control approach, but largely failed to safely identify cohorts of COPD and LC in partial or complete remission as being cancer-free in a blinded approach. The Aeonose® also showed potential in distinguishing ILD from HC in direct comparison. Our data suggest that - based on the herein applied approach of dichotomous comparison of conditions for training - relevant VOC signals originating from comorbidities such as COPD may have erroneously led to separation between LC or ILD and healthy control. Notwithstanding these somewhat disappointing results, we nevertheless believe that VOC signatures, once being adequately clustered and annotated to the underlying pulmonary phenotype, may be used for rapid and safe detection of lung cancer and ILDs and to accomplish lung cancer screening programs based on low dose CT. We suggest that artificial intelligence or principle compound analysis - based studies of a much broader data set of patients with interstitial lung diseases may be much better suitable to train these devices and ultimately to allow safe differentiation within ILDs as well as cancer and non cancer.

In the present work, a novel, portable and innovative eNose composed of a surface acoustic wave (SAW) sensor array based on zeolitic imidazolate frameworks, ZIF-8 and ZIF-67 nanocrystals (pure and combined with gold nanoparticles), as sensitive layers has been tested as a non-invasive system to detect different disease markers, such as acetone, ethanol and ammonia, related to the diagnosis and control of diabetes mellitus through exhaled breath. The sensors have been prepared by spin coating, achieving continuous sensitive layers at the surface of the SAW device. Low concentrations (5 ppm, 10 ppm and 25 ppm) of the marker analytes were measured, obtaining high sensitivities, good reproducibility, short time response and fast signal recovery., This work has been supported by Universidad Nacional Autónoma de México via Grants DGAPA-UNAM-PAPIIT TA100118 and DGAPA-UNAM-PAPIIT IT100518, the Fundación General CSIC via Programa ComFuturo, and the Spanish Ministry of Science and Innovation via Grant TEC2016-79898-C6-(AEI/FEDER,EU). This research has used the Spanish ICTS Network MICRONANOFABS (partially funded by MINECO), We acknowledge support by the CSIC Open Access Publication Initiative through its Unit of Information Resources for Research (URICI)

Fecal volatile organic compound (VOC) analysis has shown great potential as a noninvasive diagnostic biomarker for a variety of diseases. Before clinical implementation, the factors influencing the outcome of VOC analysis need to be assessed. Recent studies found that the sampling conditions can influence the outcome of VOC analysis. However, the dietary influences remains unknown, especially in (preterm) infants. Therefore, we assessed the effects of feeding composition on fecal VOC patterns of preterm infants (born at &lt, 30 weeks gestation). Two subgroups were defined: (1) daily intake &gt, 75% breastmilk (BM) feeding and (2) daily intake &gt, 75% formula milk (FM) feeding. Fecal samples, which were collected at 7, 14 and 21 days postnatally, were analyzed by an electronic nose device (Cyranose 320&reg, ). In total, 30 preterm infants were included (15 FM, 15 BM). No differences in the fecal VOC patterns were observed at the three predefined time-points. Combining the fecal VOC profiles of these time-points resulted in a statistically significant difference between the two subgroups although this discriminative accuracy was only modest (AUC [95% CI], p-value, sensitivity, and specificity of 0.64 [0.51&ndash, 0.77], 0.04, 68%, and 51%, respectively). Our results suggest that the influence of enteral feeding on the outcome of fecal VOC analysis cannot be ignored in this population. Furthermore, in both subgroups, the fecal VOC patterns showed a stable longitudinal course within the first month of life.

In recent years pollution due to hydrocarbon spills has increased markedly as a result of the numerous advances in technologies and industrial processes. Anthropogenic activities (accidental or illegal) are responsible for most of these incidents. In some cases, the spills are not detected at the moment they occur and the contaminants are subjected to different degradation phenomena that may change the chemical composition of the hydrocarbon over time. An incorrect or ineffective identification of the spill could lead to significant consequences, bearing in mind that most spills are hazardous to the environment. In the present work the capacity of the analytical technique based on the Electronic Nose (eNose) combined with chemometrics in the identification and discrimination of different weathered petroleum-derived products (PDPs) was studied. Different volumes (40 &mu, L and 80 &mu, L) of PDPs (gasoline, diesel, and paraffin) were poured onto different supports (wood, cork, paper, and cotton sheet) and subjected to a natural weathering process by evaporation for one month. The porosity of the support was also studied. The application of linear discriminant analysis allowed the full discrimination of the samples according to the presence/absence of PDP and a 97.7% of correct discrimination of the different PDPs regardless of the weathering time, support or volume used. The results show that the system is capable of detecting and discriminating the presence of petroleum-derived products in any of the situations studied.

Acute rhinosinusitis (ARS) is a sudden, symptomatic inflammation of the nasal and paranasal mucosa. It is usually caused by respiratory virus infection, but bacteria complicate for a small number of ARS patients. The differential diagnostics between viral and bacterial pathogens is difficult and currently no rapid methodology exists, so antibiotics are overprescribed. The electronic nose (eNose) has shown the ability to detect diseases from gas mixtures. Differential mobility spectrometry (DMS) is a next-generation device that can separate ions based on their different mobility in high and low electric fields. Five common rhinosinusitis bacteria (Streptococcus pneumoniae, Haemophilus influenzae, Moraxella catarrhalis, Staphylococcus aureus, and Pseudomonas aeruginosa) were analysed in vitro with DMS. Classification was done using linear discriminant analysis (LDA) and k-nearest neighbour (KNN). The results were validated using leave-one-out cross-validation and separate train and test sets. With the latter, 77% of the bacteria were classified correctly with LDA. The comparative figure with KNN was 79%. In one train-test set, P. aeruginosa was excluded and the four most common ARS bacteria were analysed with LDA and KNN; the correct classification rate was 83 and 85%, respectively. DMS has shown its potential in detecting rhinosinusitis bacteria in vitro. The applicability of DMS needs to be studied with rhinosinusitis patients.

In this work, a new generation of eNose systems particularly suited for exhaled breath gas analysis is presented. The developed analyzer system comprises a compact modular, low volume, temperature controlled sensing chamber explicitly tested for the detection of acetone, isoprene, pentane and isopropanol. The eNose system sensing chamber consists of three compartments, each of which can contain 8 analog Metal Oxide (MOX) sensors or 10 digital MOX sensors. Additional sensors within the digital compartment allow for pressure, humidity and temperature measurements. The presented eNose system contains a sensor array with up to 30 physical sensors and provides the ability to discriminate between low VOC concentrations under dry and humid conditions. The MOX sensor signals were analyzed by pattern recognition methods.

In a fire investigation the rapid detection of the presence of ignitable liquids like gasoline is of great importance as it allows appropriate treatment of the remains, the identification of prevention methods and detects the possible presence of an arsonist. In some cases, analysts cannot access the fire scene in the first few hours due to the dangers involved in the situation and, as a consequence, phenomena such as weathering start. Ignitable liquid weathering is an evaporation process that results in an increase in the abundance of non-volatile compounds relative to volatile compounds, and this process changes the chemical composition. In the present work, the weathering of samples of gasoline at different times (from 0 h to a month) has been studied using an electronic nose (eNose). The influence of the volume used (40 µL and 80 µL) and the type of support (cork, wood, paper and cotton sheet) has been studied. Chemometric tools have been used with the aim of ascertaining the weathering time for which the developed method is capable of detecting the presence of gasoline. The eNose was able to discriminate samples of weathered gasoline. The support used for the samples did not seem to have an influence on the detection and the system.

To obtain a better understanding of the complex clinical conditions and disease mechanisms of severe asthma, the Unbiased Biomarkers for the Prediction of Respiratory Disease Outcomes (U-BIOPRED) consortium was initiated. By generating multi-molecular patient profiles and revealing distinct phenotypes, the consortium aims for more accurate prediction of therapeutic efficacy, and identification of novel targets and mechanistic pathways in both adult and pediatric patients. Noninvasive metabolomics of exhaled air (breathomics) through gas-sensor driven electronic nose (eNose) technology and gas chromatography–mass spectrometry (GC-MS) were two of the many applied omics approaches during this project. Challenging study aspects such as the incorporation of multiple eNose devices and a pan-European multicenter setting led to the establishment of the U-BIOPRED eNose platform, and the development of new sampling and storage strategies of exhaled breath samples. Based on a description of adapted technologies, and by virtue of a proof of concept analysis, this chapter provides a first glimpse into the outcomes of the U-BIOPRED eNose and GC-TOF-MS datasets, combined with information about new insights and future directions for the field of breathomics.

Laktaatti on maitohapon anioni. Maitohappoasidoosiksi kutsutaan tilaa, jossa veren laktaattiarvot ovat jatkuvasti yli 5 mmol/l ja elimistössä vallitsee metabolinen asidoosi. Veren laktaattipitoisuudet kohoavat esimerkiksi rasituksessa, vakavissa infektioissa ja sydänpysähdyksen jälkeen. Laktaattipitoisuuden määrittämistä käytetään erityisesti arvioitaessa sairauden vakavuutta ja hoidon vastetta. Perinteisesti laktaattipitoisuus on määritelty verinäytteen perusteella. Ionimobiliteettispektrometri erottelee molekyylejä niiden varauksen, muodon ja massan mukaan. DMS:ssä (differential mobility spectrometry) on lisäksi muuttuva sähkökenttä. Sovelluksia näillä laitteilla on turvallisuusviranomaisilla ja lisääntyvästi myös terveydenhuollossa. Laadimme tutkimusasetelman, jossa nuoret perusterveet koehenkilöt rasittivat itseään polkupyöräergometrilla nousevin vastuksin. Rasituskoeprotokollan aikana määritettiin subjektiivinen rasitusaste ja otettiin hengitysilmanäytteitä sekä kapillaarinäytteitä laktaattipitoisuuden määrittämiseksi verestä. Hengitysilmanäyte analysoitiin sen jälkeen DMS-laitteella. Tutkimushypoteesinamme oli, että veren laktaattipitoisuudet korreloivat hengitysilmasta mitattavissa olevan laktaatin kanssa. Tutkimuksessamme laktaattipitoisuuden korrelaatio pyöräilyvastuksen kanssa oli 0.62 ja subjektiivisen rasitustason kanssa 0.81. Laktaatin havaitseminen hengitysilmasta DMS:ää käyttäen vaikuttaa mahdolliselta. Tulevaisuudessa DMS:ää voisi hyödyntää kenttäolosuhteissa nopeaan ja noninvasiiviseen laktaatin määrittämiseen. Tämän opinnäytteen alkuperäisyys on tarkastettu Turnitin OriginalityCheck-ohjelmalla Tampereen yliopiston laatujärjestelmän mukaisesti.

Tausta. Iho- ja pehmytkudosinfektiot, kuten leikkaushaavojen infektiot, ovat suhteellisen yleisiä ja aiheuttavat yhteiskunnalle merkittävää kuormitusta. Nopeaa ja kustannustehokasta menetelmää infektion aiheuttajan tunnistamiseen ei ole kehitetty. Bakteeriviljely on edullinen menetelmä, mutta tulosten valmistuminen kestää usein päiviä. Nopeampien menetelmien, kuten PCR:n ongelmana on niiden vaatimat kalliit laitteistot ja se, että ne vaativat erikoiskoulutettua henkilökuntaa. Nopean ja edullisen menetelmän puuttuessa antibioottihoito joudutaan usein aloittamaan ilman tarkempaa tietoa infektion aiheuttajasta. Menetelmät. Tutkimuksessa käytettiin elektronista nenää (eNose) yleisimpien haavainfektioita aiheuttavien bakteerien tunnistamisessa. Tutkittavat bakteerit viljeltiin petrimaljoille, ja niiden erittämää kaasuseosta analysoitiin eNosella. Tulokset. Enose kykeni erottelemaan Staphylococcus aureuksen, Streptococcus pyogeneksen, Escherichia colin, Pseudomonas aeruginosan ja Clostridium perfringensin 78 % täsmällisyydellä minuuteissa ilman edeltävää näytteiden valmistelua. Laite erotti myös metisilliiniresistentin ja metisilliinisensitiivisen S. aureuksen 83 %:n herkkyydellä ja 100 %:n tarkkuudella. Johtopäätös. Tulokset osoittavat, että eNosea voidaan käyttää bakteerien nopeaan tunnistamiseen viljelmistä. Lisäksi laite kykeni erottelemaan MRSA:n ja MSSA:n toisistaan, joten sitä voisi käyttää myös antibioottiherkkyyden määrittämiseen.

Electronic nose (eNose) systems are particularly appreciated for their portability, usability, relative low cost, and real-time or near real-time response. Their application finds space in several domains, including environmental monitoring. Within this field, marine monitoring is of particular scientific relevance due to the fragility of this specific environment, daily threatened by human activities that can potentially bring to catastrophic and irreversible consequences on marine wildlife. Under such considerations, a systematic review, complying with the PRISMA guidelines, was conducted covering the period up to 15 October 2018, in PubMed, ScienceDirect, and Google Scholar. Despite the relatively low number of articles published on this specific topic and the heterogeneity of the technological approaches employed, the results obtained by the various groups highlight the positive contribution eNose has given and can provide in near future for the monitoring and safeguarding of this delicate environment.

Respiratory infections, viral or bacterial, are a common cause of acute exacerbations of chronic obstructive pulmonary disease (AECOPD). A rapid, point-of-care, and easy-to-use tool distinguishing viral and bacterial from other causes would be valuable in routine clinical care. An electronic nose (e-nose) could fit this profile but has never been tested in this setting before. In a single-center registered trial (NTR 4601) patients admitted with AECOPD were tested with the Aeonose (R) electronic nose, and a diagnosis of viral or bacterial infection was obtained by bacterial culture on sputa and viral PCR on nose swabs. A neural network with leave-10%-out cross-validation was used to assess the e-nose data. Forty three patients were included. In the bacterial infection model, 22 positive cases were tested versus the negatives; and similarly 18 positive cases were tested in the viral infection model. The Aeonose was able to distinguish between COPD-subjects suffering from a viral infection and COPD patients without infection, showing an area under the curve (AUC) of 0.74. Similarly, for bacterial infections, an AUC of 0.72 was obtained. The Aeonose e-nose yields promising results in 'smelling' the presence or absence of a viral or bacterial respiratory infection during an acute exacerbation of COPD. Validation of these results using a new and large cohort is required before introduction into clinical practice.

[EN] Nowadays, new technologies tend to evolve to a concept known as the cloud. The cloud is a concept that gives name to both the provided apps and services, and the hardware and software on the datacenters that provide those services. The main goal of the following thesis is to explain the theoretical foundations and the procedures followed for the development of a web application that will be used for data processing on an eNose. This eNose is based on another electronic nose provided with thirtytwo gas sensors. The original device uses a National Instruments data acquisition card and a computer provided with LabVIEW programmed software for the data monitoring and storage. The main concern of the contemporary engineering is energy saving and resources optimization. From this point, it is proposed to design an eNose with only four gas sensors that can be acquirable through a low consuming embedded prototype. Another important principle is the usage of free open tools, such as GNU Linux systems, and developed software through languages like Python or Java, [ES] Actualmente, las nuevas tecnologías tienden a evolucionar hacia un concepto llamado la nube. La nube es un concepto que se refiere tanto a las aplicaciones entregadas como servicios en Internet como al hardware y sistemas de software en los centros de datos que prestan estos servicios. La actual tesina tiene como objetivo explicar las bases teóricas necesarias y los procedimientos seguidos para el desarrollo de una aplicación web que será utilizada para el tratamiento de datos en la nube de un eNose. Este eNose se basa en otra nariz electrónica con treinta y dos sensores de gas. El dispositivo original utiliza una tarjeta de adquisición de datos de National Instruments para la parte de adquisición de los sensores y un ordenador con un software programado en LabVIEW para la parte de monitorización y almacenamiento de los datos. La principal preocupación en la actualidad de la ingeniería electrónica es el bajo consumo y la optimización de recursos. Con esta base se propone diseñar un eNose con sólo cuatro sensores de gas, que sea adquirible mediante un prototipo empotrado de bajo consumo. Otro punto importante es la utilización de herramientas (hardware y software) libres, como sistemas GNU Linux y software desarrollado mediante lenguajes libres como Python o Java.

Currently, many different methods are being used for pre-processing, statistical analysis and validation of data obtained by electronic nose technology from exhaled air. These various methods, however, have never been thoroughly compared. We aimed to empirically evaluate and compare the influence of different dimension reduction, classification and validation methods found in published studies on the diagnostic performance in several datasets. Our objective was to facilitate the selection of appropriate statistical methods and to support reviewers in this research area. We reviewed the literature by searching Pubmed up to the end of 2014 for all human studies using an electronic nose and methodological quality was assessed using the QUADAS-2 tool tailored to our review. Forty-six studies were evaluated regarding the range of different approaches to dimension reduction, classification and validation. From forty-six reviewed articles only seven applied external validation in an independent dataset, mostly with a case-control design. We asked their authors to share the original datasets with us. Four of the seven datasets were available for re-analysis. Published statistical methods for eNose signal analysis found in the literature review were applied to the training set of each dataset. The performance (area under the receiver operating characteristics curve (ROC-AUC)) was calculated for the training cohort (in-set) and after internal validation (leave-one-out cross validation). The methods were also applied to the external validation set to assess the external validity of the performance. Risk of bias was high in most studies due to non-random selection of patients. Internal validation resulted in a decrease in ROC-AUCs compared to in-set performance: -0.15,-0.14,-0.1,-0.11 in dataset 1 through 4, respectively. External validation resulted in lower ROC-AUC compared to internal validation in dataset 1 (-0.23) and 3 (-0.09). ROC-AUCs did not decrease in dataset 2 (+0.07) and 4 (+0.04). No single combination of dimension reduction and classification methods gave consistent results between internal and external validation sets in this sample of four datasets. This empirical evaluation showed that it is not meaningful to estimate the diagnostic performance on a training set alone, even after internal validation. Therefore, we recommend the inclusion of an external validation set in all future eNose projects in medicine.

Artificial olfaction has the potential to revolutionise medical diagnosis, speed up threat detection, and provide long-term data collection on atmospheric pollution. Current technology provides a means to detect some compounds, but detection speed is slow, and accuracy is often balanced against cost and reusability of devices. Insects have long been the inspiration for artificial olfaction and are able to detect low concentrations of compounds over vast areas and navigate towards these targets. A deeper understanding of how this is achieved could inform the design of better artificial olfactory devices. What features of the insect olfactory system allow the rapid detection of miniscule concentrations of a wide variety of compounds? How does an insect discriminate odours using a limited number of olfactory receptor types?Using UAS/GAL4 technology, Drosophila melanogaster larvae expressing only a single functional olfactory sensory neuron (OSN), of their full repertoire of 21, were used to explore peripheral olfactory responses. Three different fly lines, which each expressed different olfactory receptor (OR) types, were used to record the electrophysiological responses of the peripheral OSNs to a panel of biologically significant odours, at differing concentrations. These responses were compared to those from a leading electronic nose (metal oxide sensors) for the same odour conditions, and the features of the responses were characterised. A novel odour delivery system was also developed to accurately deliver these odours and concentrations repeatably, and was validated using a commercially available photoionisation detector.The ability to correctly select the odour from which a response was recorded, out of a choice of five odours, at two concentrations each, was scrutinised using a classifier algorithm. The three OSN types achieved 53%, 62% and 75% accuracy, respectively. This is the first instance that Drosophila larvae have been conclusively shown to be able to discriminate odour concentrations using only a single peripheral OSN. The two metal oxide sensors achieved 92% and 95% accuracy under the same conditions. Whilst the features of the responses used to discriminate odours differed between the biological and electronic systems, the time frame required for correct classification of sensor data was only, in some cases, three seconds longer than in OSNs (~0.5 seconds), indicating that metal oxide sensors may have a useful role to play in biologically inspired artificial olfaction. An artificial sense of smell can allow us to safely detect disease, track down explosives and monitor air pollution. The current sensors we have for this task are expensive, slow or inaccurate. Insects have a highly advanced sense of smell, which allows them to detect tiny amounts of odours across vast distances and they can track them to their source. How can they do this with only a very limited number of smell cell types?Using genetics, all but one of the fruit fly maggot’s 21 smell cell types were switched off. The electrical activity produced from that single remaining smell cell could then be recorded, when the maggot was presented with an odour, using a highly sensitive volt-meter. This allowed a map of what different odours smelled like, to the maggot’s nervous system, to be created. As well as different odours, different concentrations (strong and weak) were also recorded. The same range of smells was also presented to an electronic version of the maggot’s nose (eNose) and the responses were recorded.A computer program then used the responses from all the odours and concentrations from the maggot and eNose, to try and decide which odour a response came from when it was given the choice from all of them. Overall, using the eNose responses, the computer performed better than with the maggot responses, meaning the eNose would be useful as a way to detect odours that change in concentration quickly within the atmosphere.

Monitoring for pollutants in potable water is an area of interest and concern for water supply companies. Supply of sub-standard water can draw complaints from public and industrial customers. Water and water tainted with pollutants were used to assess the application of a non-specific chemical sensor array (eNose) to monitor for changes in the headspace generated from a flow-cell by means of statistically designed experiments. 2-chlorophenol and diesel were used to further assess trends in headspace generation during trials where different combinations of sampling parameters were applied. Field trials were conducted in accordance with the most suitable methodology determined during initial studies under laboratory conditions. The headspace is generated by bubbling nitrogen through the flow-cell containing a water sample. The liquid sample is flushed and regenerated after each sensor acquisition cycle. The resultant headspace sample is transferred to the sensor array module where the resistance of the conducting polymer sensors is monitored as they are exposed to each respective headspace sample. The change in each sensor resistance after 60 seconds of exposure is used to represent the headspace character. Subsequent acquisitions are added to a data set and then presented graphically. Sudden changes in the sensor resistance plots represent changes in water quality. The results showed that the developed apparatus and sampling methodology can determine the presence or absence of pollution in a water matrix. Laboratory analysis showed that detection levels for 2-chlorophenol and diesel were both