Repositori institucional URV
| URV's Author/s: | Llobet Valero, Eduard |
| Author, as appears in the article.: | Zaim O; Diouf A; El Bari N; Lagdali N; Benelbarhdadi I; Ajana FZ; Llobet E; Bouchikhi B |
| Author's mail: | eduard.llobet@urv.cat |
| Author identifier: | 0000-0001-6164-4342 |
| Journal publication year: | 2021 |
| Publication Type: | Journal Publications |
| APA: | Zaim O; Diouf A; El Bari N; Lagdali N; Benelbarhdadi I; Ajana FZ; Llobet E; Bouchikhi B (2021). Comparative analysis of volatile organic compounds of breath and urine for distinguishing patients with liver cirrhosis from healthy controls by using electronic nose and voltammetric electronic tongue. Analytica Chimica Acta, 1184(), -. DOI: 10.1016/j.aca.2021.339028 |
| Papper original source: | Analytica Chimica Acta. 1184 |
| Abstract: | Advanced stage detection of liver cirrhosis (LCi) would lead to high mortality rates in patients. Therefore, accurate and non-invasive tools for its early detection are highly needed using human emanations that may reflect this disease. Human breath, along with urine and blood, has long been one of the three main biological media for assessing human health and environmental exposure. The primary objective of this study was to explore the potential of using volatile organic compounds (VOCs) assay of exhaled breath and urine samples for the diagnosis of patients with LCi and healthy controls (HC). For this purpose, we used a hybrid electronic nose (E-nose) combining two sensor families, consisting of an array of five commercial chemical gas sensors and six interdigitated chemical gas sensors based on pristine or metal-doped WO3 nanowires for sensing volatile gases in exhaled breath. A voltammetric electronic tongue (VE-tongue), composed of five working electrodes, was dedicated to the analysis of urinary VOCs using cyclic voltammetry as a measurement technique. 54 patients were recruited for this study, comprising 22 patients with LCi, and 32 HC. The two-sensing systems coupled with pattern recognition methods, namely Principal Component Analysis (PCA) and Discriminant Function Analysis (DFA), were trained to classify data clusters associated with the health status of the two groups. The diagnostic performances of the E-nose and VE-tongue systems were studied by using the receiver operating characteristic (ROC) method. The use of the E-nose or the VE-tongue separately, trained with these appropriate classifiers, showed a slight overlap indicating no clear discrimination between LCi patients and HC. To improve the performance of both electronic sensing devices, an emerging strategy, namely a multi-sensor data fusion technique, was proposed as a second aim to overcome this shortcoming. The data fusion approach of the two systems, at a medium level of abstraction, has demonstrated the ability to assess human health and disease status using non-invasive screening tools based on exhaled breath and urinary VOC analysis. This suggests that exhaled breath as well as urinary VOCs are specific to a disease state and could potentially be used as diagnostic methods. |
| Article's DOI: | 10.1016/j.aca.2021.339028 |
| Link to the original source: | https://www.sciencedirect.com/science/article/abs/pii/S0003267021008540 |
| Papper version: | info:eu-repo/semantics/acceptedVersion |
| licence for use: | https://creativecommons.org/licenses/by/3.0/es/ |
| Department: | Enginyeria Electrònica, Elèctrica i Automàtica |
| Licence document URL: | https://repositori.urv.cat/ca/proteccio-de-dades/ |
| Thematic Areas: | Spectroscopy Química Odontología Medicina ii Medicina i Materiais Matemática / probabilidade e estatística Interdisciplinar Geociências General medicine Farmacia Environmental chemistry Engenharias iv Engenharias iii Engenharias ii Enfermagem Ciências biológicas iii Ciências biológicas ii Ciências biológicas i Ciências agrárias i Ciência de alimentos Ciência da computação Chemistry, analytical Biotecnología Biodiversidade Biochemistry Astronomia / física Analytical chemistry |
| Keywords: | Volatile organic compounds Urine analysis Trace-elements Liver cirrhosis Exhaled breath analysis Electronic sensing system Data fusion zinc volatile organic compounds urine analysis identification gene exhaled breath analysis exhaled breath electronic sensing system disease discrimination data fusion cancer biomarkers |
| Entity: | Universitat Rovira i Virgili |
| Record's date: | 2024-07-27 |
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