Detection of Asymptomatic Nigrostriatal Dopaminergic Lesion in Rats by Exhaled Air Analysis Using Carbon Nanotube Sensors

Abstract The development and studies related to carbon nanotubes, due to their physical properties and small sizes, are revealing new applications in the medical field. The present paper is proposing a non-invasive method of patient glycemia measurement by mean of carbon nanotubes based sensor. Due to their small sizes and elastic properties, carbon nanotubes are able to oscillate under the weight of small molecules capable of fixing on their body structure. After piezoelectric activation, the carbon nanotubes sensor based, is able to detect the variation of oscillations produced in nanotubes due to acetone molecules diffused through a selectively permeable membrane from the exhaled air, and attached to the nanotubes. The mathematical model taken into accont shows a linear dependence between the concentration of acetone in blood and glycemia, and makes the carbon nanotube sensor suitable for indirect estimation of the glycemia by noninvasive measurements made on the exhaled air sample, providing zero risk for the patient and absence of stress during the measurements.

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Exhaled Air Analysis in Patients with Different Lung Diseases Using Artificial Odour Sensors

Proceedings of the Latvian Academy of Sciences Section B Natural Exact and Applied Sciences ◽

10.2478/v10046-009-0043-4 ◽

2009 ◽

Vol 63 (4-5) ◽

pp. 210-213

Author(s):

Immanuels Taivans ◽

Normunds Jurka ◽

Līga Balode ◽

Māris Bukovskis ◽

Uldis Kopeika ◽

...

Keyword(s):

Lung Cancer ◽

Lung Diseases ◽

Clinical Medicine ◽

Chronic Obstructive ◽

Exhaled Breath ◽

Air Pollution Control ◽

Air Analysis ◽

Artificial Nose ◽

Chronic Lung Diseases ◽

Exhaled Air

Exhaled Air Analysis in Patients with Different Lung Diseases Using Artificial Odour Sensors Sniffing breath to diagnose a disease has been practiced by doctors since ancient times. Nowadays, electronic noses are successfully used in the food, textile and perfume industry as well as for air pollution control. The aim of this study was to test whether exhaled breath analysed by an artificial nose could identify and discriminate between different lung diseases. A total of 76 individuals were tested: 25 bronchial asthma, 19 lung cancer, 10 pneumonia, 6 chronic obstructive pulmonary disease (COPD) patients and 16 healthy volunteers. Exhaled air was collected in plastic bags and immediately analysed using an electronic nose instrument (9185, Nordic Sensors AB) containing 14 different odour sensors. Multifactor logistic regression analysis was used to determine correlation between the amplitudes of sensor responses and the clinical diagnoses of patients and to calculate sensitivity and specificity of the method for each diagnosis. For diagnostics of asthma the sensitivity was found to be 84% and specificity — 86%. For lung cancer, the sensitivity was 74% and specificity, 95%; for pneumonia 90% and 98%, but for COPD, 33% and 97%, respectively. We conclude that an artificial nose is able to discriminate among different lung diseases with sufficiently good accuracy. This method may be further developed to implement it in clinical medicine for express diagnostics of acute and chronic lung diseases.

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