SAMPLING AND SENSING STRATEGIES FOR NOVEL APPLICATIONS WITH AN ARTIFICIAL OLFACTORY SYSTEM

L’utilizzo dei cinque sensi, di cui ognuno di noi è normalmente dotato, ci permette quotidianamente di percepire ed interpretare il mondo che ci circonda, molto spesso senza aver coscienza di farne uso, ma semplicemente sfruttando i risultati che ne otteniamo per l’interazione con l’ambiente circostante. L’olfatto è probabilmente uno dei sensi del quale l’essere umano, nella sua evoluzione, ha perso maggiormente la capacità di sfruttare al massimo le potenzialità. Tuttavia l’odore rappresenta una importante sorgente di informazioni, grazie alla capacità di sintesi di una serie di parametri e di interazioni che noi non siamo in grado di raccogliere, interpretare ed elaborare contemporaneamente. L’oggetto di questa tesi è il naso elettronico realizzato presso i laboratori del Gruppo Sensori e Microsistemi dell’Università degli Studi di Roma ‘Tor Vergata’. L’obiettivo del lavoro è quello di individuare le problematiche fondamentali relative all’utilizzo di questa tecnologia e, tramite lo studio delle possibili soluzioni, raggiungere un generale perfezionamento dell’intero sistema. Sono svariati i campi nei quali le grandi potenzialità di un sistema olfattivo artificiale possono trovare utile applicazione. La caratteristica multidisciplinare di un così differenziato ventaglio di applicazioni, richiede la progettazione di una serie di sistemi di campionamento specifici per ogni scopo. Sebbene il cuore dell’intero sistema consista nei suoi principi di funzionamento e nel tipo di materiale sensibile utilizzato, il campionamento riveste una importanza fondamentale all’interno della catena di misura, perché attraverso la sua ottimizzazione si rende possibile un efficace utilizzo dello strumento nella pratica dei problemi reali relativi ai diversi campi. Proprio per questa ragione, il modo migliore di operare è quello di progettare dei protocolli sperimentali ‘ad hoc’ specifici per ogni applicazione. In questa tesi sono considerate tre differenti sperimentazioni: applicazioni in campo medico ed ambientale, e campionamento dell’odore in condizioni statiche. In particolare viene presentata l’esperienza di sei anni di sperimentazioni relative allo studio del tumore al polmone tramite l’analisi dell’espirato per mezzo del naso elettronico.Everyday, everyone of us uses the five senses, very often without consciousness at all of using them, but simply exploiting the results. The results consist in an interpretation of the real world around us. Olfaction is probably one of the senses humans have lost potentiality to exploit during evolution, but odour is a very important source of data, because of the power of synthesis of a lot of interactions and parameters we are not able to collect, read and elaborate at the same time. An existing technology, the Electronic Nose of the Sensors and Microsystems Group of the University of Rome ‘Tor Vergata’, is the objective of this Thesis. The aim is to ask fundamental questions about it, and by studying the possible solutions, reach the whole system improvement. The great potentialities of artificial olfactory systems can be exploited in many fields. This multidisciplinary range of applications asks for designing of dedicated sampling systems depending on the different scope. Although the working principle and the sensitive material are the basis on which these devices are developed, the sampling, within the measure chain, is a fundamental step to optimize the whole system performances. According to these considerations the best way for designing “ad hoc“ experimental set is to specialize a specific sampling procedure for each application. In this thesis three different studies are considered: medical and environmental applications, and odour sampling in static conditions. In particular, the experience of the six years of experiments dedicated to lung cancer study by mean of e-nose breath analysis is illustrated

Smart Device for the Determination of Heart Rate Variability in Real Time

This work presents a first approach to the design, development, and implementation of a smart device for the real-time measurement and detection of alterations in heart rate variability (HRV). The smart device follows a modular design scheme, which consists of an electrocardiogram (ECG) signal acquisition module, a processing module and a wireless communications module. From five-minute ECG signals, the processing module algorithms perform a spectral estimation of the HRV. The experimental results demonstrate the viability of the smart device and the proposed processing algorithms.Fundación Pública Andaluza Progreso y Salud. Gobierno de Andalucía PI-0010-2013 y PI-0041-2014Ministerio de Economía y Competitividad (Instituto de Salud Carlos III) PI15 / 00306 y DTS15 / 00195CIBER-BBN INT-2-CAR

Chemical Sensor for Haemodialysis Application

Abstract The water used to supply a haemodialysis center requires particular mode of treatment in order to achieve the best technical, economic and therapeutic distribution. Dialysis patients come in contact weekly with a large amount of water through the dialysis apparatus. It is therefore essential that this solution has a high quality and purity in terms of proper electrolyte composition, low concentration or absence of organic and inorganic chemical pollutants, low concentration or absence of bacteria, yeasts, fungi and endotoxins. The chemical and microbiological quality of water intended for medical and biomedical treatments, such as haemodialysis, is generally defined on the basis of a plurality of international reference standards (ASTM International standards D1193 and D5196; International Pharmacopoeia and European Pharmacopoeia CAP / NCCLS 1988). In this work the authors have designed an electrochemical device used to characterize pure and ultrapure water for biomedical applications (Patent: TO2014A000765). The results obtained show a good ability of the device in the discrimination of different bacteria and of their concentration (CFU); Pseudomonas and E-coli have been here tested

A Novel Approach for Prostate Cancer Diagnosis using a Gas Sensor Array

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Elevated risks of death for diabetes mellitus and cardiovascular diseases in Italian AIDS cases

After the introduction of highly active antiretroviral therapies (HAART), an increased incidence of insulin resistance, diabetes mellitus (DM), and cardiovascular diseases has been described. The impact of such conditions on mortality in the post-HAART era has been also assessed in various modes in the literature. In this paper, we report on the death risks for DM, myocardial infarction, and chronic ischemic heart diseases that were investigated among 9662 Italian AIDS cases diagnosed between 1999 and 2005. Death certificates reporting DM, myocardial infarction, and chronic ischemic heart diseases were reviewed to identify the underlying cause of death, and to compare the observed numbers of deaths with the expected ones from the sex- and age-matched, general population of Italy. Person-years at risk of death were computed from date of AIDS diagnosis up to date of death or to December 31, 2006. Standardized mortality ratios (SMR) and their 95% confidence intervals (CI) were computed. DM and cardiovascular diseases were the cause of death for 43 out of 3101 deceased AIDS cases (i.e., 1.4% of all deaths). In comparison with the general population, the risks of death were 6.4-fold higher for DM (95% CI:3.5-10.8), 2.3-fold higher for myocardial infarction (95% CI:1.4-3.7) and 3.0 for chronic ischemic heart diseases (95% CI: 1.5-5.2)

FIRB "SQUARE" project: nano-structured sensors for the detection of the polluting in engine exhaust gases and for indoor air quality monitoring

The present work is a final dissemination of activities carried out and main results obtained in the national founded project Firb "Square". The project is leaded by Centro Ricerche Fiat and it involves the most qualified national public Research Institutes and Universities active in the fields of nanomaterials synthesis, nanotechnology and gas sensors development

GC-MS metabolomics-based approach for the identification of a potential VOC-biomarker panel in the urine of renal cell carcinoma patients

The analysis of volatile organic compounds (VOCs) emanating from biological samples appears as one of the most promising approaches in metabolomics for the study of diseases, namely cancer. In fact, it offers advantages, such as non-invasiveness and robustness for high-throughput applications. The purpose of this work was to study the urinary volatile metabolic profile of patients with renal cell carcinoma (RCC) (n = 30) and controls (n = 37) with the aim of identifying a potential specific urinary volatile pattern as a non-invasive strategy to detect RCC. Moreover, the effect of some confounding factors such as age, gender, smoking habits and body mass index was evaluated as well as the ability of urinary VOCs to discriminate RCC subtypes and stages. A headspace solid-phase microextraction/gas chromatography-mass spectrometry-based method was performed, followed by multivariate data analysis. A variable selection method was applied to reduce the impact of potential redundant and noisy chromatographic variables, and all models were validated by Monte Carlo cross-validation and permutation tests. Regarding the effect of RCC on the urine VOCs composition, a panel of 21 VOCs descriptive of RCC was defined, capable of discriminating RCC patients from controls in principal component analysis. Discriminant VOCs were further individually validated in two independent samples sets (nine RCC patients and 12 controls, seven RCC patients with diabetes mellitus type 2) by univariate statistical analysis. Two VOCs were found consistently and significantly altered between RCC and controls (2-oxopropanal and, according to identification using NIST14, 2,5,8-trimethyl-1,2,3,4-tetrahydronaphthalene-1-ol), strongly suggesting enhanced potential as RCC biomarkers. Gender, smoking habits and body mass index showed negligible and age-only minimal effects on the urinary VOCs, compared to the deviations resultant from the disease. Moreover, in this cohort, the urinary volatilome did not show ability to discriminate RCC stages and histological subtypes. The results validated the value of urinary volatilome for the detection of RCC and advanced with the identification of potential RCC urinary biomarkers.info:eu-repo/semantics/publishedVersio

Discrimination between oral corticosteroid-treated and oral corticosteroid-non-treated severe asthma patients by an electronic nose platform

Rationale: Some severe asthma patients require oral corticosteroids (OCS) likely due to greater disease severity. Exhaled molecular markers can provide phenotypic information in asthma. Objectives: Determine whether patients on OCS (OCS+) have a different breathprint compared with those who were not on OCS (OCS-); determine the classification accuracy of eNose as compared to FEV1 % pred, % sputum eosinophils, and exhaled nitric oxide (FENO). Methods: This was a cross-sectional analysis of the U-BIOPRED cohort. Severe asthma was defined by IMI-criteria [Bel Thorax 2011]. OCS+ patients had daily OCS. OCS- patients had never had OCS and were on maintenance inhaled fluticasone equivalent >1000 μg/day. Exhaled volatile organic compounds trapped on adsorption tubes were analysed by centralized eNose platform (Owlstone Lonestar, Cyranose 320, Comon Invent, Tor Vergata TEN) including a total of 190 sensors. t test was used for comparing groups and support vector machine with leave-one-out cross-validation as a classifier. Results: 33 OCS+ (age 55±11yr, mean±SD, 52% female, 27% smokers, pre-bronchodilator FEV1 64.1±24% pred) and 40 OCS- severe asthma patients (age 54±15yr, mean±SD, 55% female, 35% smokers, pre-bronchodilator FEV1 61.8±24% pred) were studied. Sensor by sensor analysis showed that 56 sensors provided different mean values (change in sensor resistance or frequency) between groups (P<0.05). Accuracy of classification was as follows: eNose 71% (n=73), FENO 71% (n=70), FEV1 62% (n=73) and sputum eosinophils 59% (n=37). Conclusions: Preliminary results suggest OCS+ and OCS- severe asthma patients can be distinguished by an eNose platform

Breathomics can discriminate between anti IgE-treated and non-treated severe asthma adults

Rationale: Omalizumab, an anti-IgE monoclonal antibody, is indicated in adults with severe persistent allergic asthma. Exhaled molecular markers can provide phenotypic information in asthma. Objectives: Determine whether adults with severe asthma on omalizumab (anti-IgE+) have a different breathprint compared with those who were not on anti-IgE therapy (anti-IgE-) as assessed by eNoses and gas chromatography/mass spectrometry (GC/MS) (breathomics). Methods: This was a cross-sectional analysis of the U- BIOPRED adult cohort. Severe asthma was defined by IMI-criteria [Bel, Thorax 2011]. Anti-IgE+ patients were on a regular treatment with s.c. omalizumab (150-375 mg) every 2-4 weeks. Exhaled volatile compounds trapped on adsorption tubes were analysed by a centralized eNose platform (Owlstone Lonestar, two Cyranose 320, Comon Invent, Tor Vergata TEN), including a total of 190 sensors, and GC/MS. Recursive feature elimination (http://topepo.github.io/caret/rfe.html) was used for feature selection and random forests, more robust to overfitting, for classification. Results: 9 anti- IgE+ (females/males 2/7, age 52.6±16.3 years, mean±SD, 1/2/6 current/ex/nonsmokers, pre-bronchodilator FEV1 70.6±21.1% predicted value) and 30 anti-IgE- patients (18/12 females/males, age 53.2±14.2 years, 0/16/14 current/ex/nonsmokers, pre-bronchodilator FEV1 59.6±30.7% predicted value) were studied. Conclusions: Preliminary results suggest that breathomics can distinguish between anti-IgE+ and anti-IgE- severe asthma patients