scholarly journals Non-Invasive Method to Detect Infection with Mycobacterium tuberculosis Complex in Wild Boar by Measurement of Volatile Organic Compounds Obtained from Feces with an Electronic Nose System

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 584
Author(s):  
Kelvin de Jesús Beleño-Sáenz ◽  
Juan Martín Cáceres-Tarazona ◽  
Pauline Nol ◽  
Aylen Lisset Jaimes-Mogollón ◽  
Oscar Eduardo Gualdrón-Guerrero ◽  
...  
Keyword(s):  
Volatile Organic Compounds ◽  
Wild Boar ◽  
Organic Compounds ◽  
Electronic Nose ◽  
Bovine Tuberculosis ◽  
Human Beings ◽  
Non Invasive ◽  
Testing Phase ◽  
Volatile Organic ◽  
Electronic Nose System

More effective methods to detect bovine tuberculosis, caused by Mycobacterium bovis, in wildlife, is of paramount importance for preventing disease spread to other wild animals, livestock, and human beings. In this study, we analyzed the volatile organic compounds emitted by fecal samples collected from free-ranging wild boar captured in Doñana National Park, Spain, with an electronic nose system based on organically-functionalized gold nanoparticles. The animals were separated by the age group for performing the analysis. Adult (>24 months) and sub-adult (12–24 months) animals were anesthetized before sample collection, whereas the juvenile (<12 months) animals were manually restrained while collecting the sample. Good accuracy was obtained for the adult and sub-adult classification models: 100% during the training phase and 88.9% during the testing phase for the adult animals, and 100% during both the training and testing phase for the sub-adult animals, respectively. The results obtained could be important for the further development of a non-invasive and less expensive detection method of bovine tuberculosis in wildlife populations.

scholarly journals Non-Invasive Diagnosis of Diabetes by Volatile Organic Compounds in Urine Using FAIMS and Fox4000 Electronic Nose

Biosensors ◽  
2018 ◽  
Vol 8 (4) ◽  
pp. 121 ◽  
Author(s):  
Siavash Esfahani ◽  
Alfian Wicaksono ◽  
Ella Mozdiak ◽  
Ramesh Arasaradnam ◽  
James Covington
Keyword(s):  
Volatile Organic Compounds ◽  
Organic Compounds ◽  
Electronic Nose ◽  
Area Under The Curve ◽  
Urine Samples ◽  
Support Vector ◽  
Sparse Logistic Regression ◽  
Non Invasive ◽  
Volatile Organic ◽  
Sample Age

The electronic nose (eNose) is an instrument designed to mimic the human olfactory system. Usage of eNose in medical applications is more popular than ever, due to its low costs and non-invasive nature. The eNose sniffs the gases and vapours that emanate from human waste (urine, breath, and stool) for the diagnosis of variety of diseases. Diabetes mellitus type 2 (DM2) affects 8.3% of adults in the world, with 43% being underdiagnosed, resulting in 4.9 million deaths per year. In this study, we investigated the potential of urinary volatile organic compounds (VOCs) as novel non-invasive diagnostic biomarker for diabetes. In addition, we investigated the influence of sample age on the diagnostic accuracy of urinary VOCs. We analysed 140 urine samples (73 DM2, 67 healthy) with Field-Asymmetric Ion Mobility Spectrometry (FAIMS); a type of eNose; and FOX 4000 (AlphaM.O.S, Toulouse, France). Urine samples were collected at UHCW NHS Trust clinics over 4 years and stored at −80 °C within two hours of collection. Four different classifiers were used for classification, specifically Sparse Logistic Regression, Random Forest, Gaussian Process, and Support Vector on both FAIMS and FOX4000. Both eNoses showed their capability of diagnosing DM2 from controls and the effect of sample age on the discrimination. FAIMS samples were analysed for all samples aged 0–4 years (AUC: 88%, sensitivity: 87%, specificity: 82%) and then sub group samples aged less than a year (AUC (Area Under the Curve): 94%, Sensitivity: 92%, specificity: 100%). FOX4000 samples were analysed for all samples aged 0–4 years (AUC: 85%, sensitivity: 77%, specificity: 85%) and a sub group samples aged less than 18 months: (AUC: 94%, sensitivity: 90%, specificity: 89%). We demonstrated that FAIMS and FOX 4000 eNoses can discriminate DM2 from controls using urinary VOCs. In addition, we showed that urine sample age affects discriminative accuracy.

Discriminative detection of volatile organic compounds using an electronic nose based on TiO2 hybrid nanostructures

2021 ◽  
pp. 130124
Author(s):  
Patrick P. Conti ◽  
Rafaela S. Andre ◽  
Luiza A. Mercante ◽  
Lucas Fugikawa-Santos ◽  
Daniel S. Correa
Keyword(s):  
Volatile Organic Compounds ◽  
Organic Compounds ◽  
Electronic Nose ◽  
Hybrid Nanostructures ◽  
Volatile Organic

scholarly journals Influence of age and gender on the profile of exhaled volatile organic compounds analyzed by an electronic nose

2016 ◽  
Vol 42 (2) ◽  
pp. 143-145 ◽  
Author(s):  
Silvano Dragonieri ◽  
Vitaliano Nicola Quaranta ◽  
Pierluigi Carratu ◽  
Teresa Ranieri ◽  
Onofrio Resta
Keyword(s):  
Volatile Organic Compounds ◽  
Organic Compounds ◽  
Electronic Nose ◽  
Principal Component ◽  
Exhaled Breath ◽  
Age And Gender ◽  
Volatile Organic ◽  
Older Subjects ◽  
Never Smokers ◽  
And Gender

We aimed to investigate the effects of age and gender on the profile of exhaled volatile organic compounds. We evaluated 68 healthy adult never-smokers, comparing them by age and by gender. Exhaled breath samples were analyzed by an electronic nose (e-nose), resulting in "breathprints". Principal component analysis and canonical discriminant analysis showed that older subjects (≥ 50 years of age) could not be distinguished from younger subjects on the basis of their breathprints, as well as that the breathprints of males could not distinguished from those of females (cross-validated accuracy, 60.3% and 57.4%, respectively).Therefore, age and gender do not seem to affect the overall profile of exhaled volatile organic compounds measured by an e-nose.

scholarly journals Flexible Impedimetric Electronic Nose for High-Accurate Determination of Individual Volatile Organic Compounds by Tuning the Graphene Sensitive Properties

Chemosensors ◽  
2021 ◽  
Vol 9 (12) ◽  
pp. 360
Author(s):  
Tianqi Lu ◽  
Ammar Al-Hamry ◽  
José Mauricio Rosolen ◽  
Zheng Hu ◽  
Junfeng Hao ◽  
...  
Keyword(s):  
Volatile Organic Compounds ◽  
Organic Compounds ◽  
Electronic Nose ◽  
Accurate Determination ◽  
Identification Accuracy ◽  
Structural Defects ◽  
Support Vector ◽  
Volatile Organic ◽  
Variable Sensitivity ◽  
Relative Change

We investigated functionalized graphene materials to create highly sensitive sensors for volatile organic compounds (VOCs) such as formaldehyde, methanol, ethanol, acetone, and isopropanol. First, we prepared VOC-sensitive films consisting of mechanically exfoliated graphene (eG) and chemical graphene oxide (GO), which have different concentrations of structural defects. We deposited the films on silver interdigitated electrodes on Kapton substrate and submitted them to thermal treatment. Next, we measured the sensitive properties of the resulting sensors towards specific VOCs by impedance spectroscopy. We obtained the eG- and GO-based electronic nose composed of two eG films- and four GO film-based sensors with variable sensitivity to individual VOCs. The smallest relative change in impedance was 5% for the sensor based on eG film annealed at 180 °C toward 10 ppm formaldehyde, whereas the highest relative change was 257% for the sensor based on two-layers deposited GO film annealed at 200 °C toward 80 ppm ethanol. At 10 ppm VOC, the GO film-based sensors were sensitive enough to distinguish between individual VOCs, which implied excellent selectivity, as confirmed by Principle Component Analysis (PCA). According to a PCA-Support Vector Machine-based signal processing method, the electronic nose provided identification accuracy of 100% for individual VOCs. The proposed electronic nose can be used to detect multiple VOCs selectively because each sensor is sensitive to VOCs and has significant cross-selectivity to others.

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