| 1. |
- Pavlou, AK, et al.
(författare)
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An intelligent rapid odour recognition model in discrimination of Helicobacter pylori and other gastroesophageal isolates in vitro
- 2000
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Ingår i: Biosensors & bioelectronics. - : Elsevier Science B.V., Amsterdam.. - 0956-5663 .- 1873-4235. ; 15:08-jul, s. 333-342
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Tidskriftsartikel (refereegranskat)abstract
- Two series of experiments are reported which result in the discrimination between Helicobacter pylori and other bacterial gastroesophageal isolates using a newly developed odour generating system, an electronic nose and a hybrid intelligent odour recognition system. In the first series of experiments, after 5 h of growth (37 degreesC), 53 volatile sniffs were collected over the headspace of complex broth cultures of the following clinical isolates: Staphylococcus aureus, Klebsiella sp., H. pylori, Enterococcus faecalis (10(7) ml(-1)), Mixed infection (Proteus mirabilis, Escherichia coli, and E. faecalis 3 x 10(6) mi each) and sterile cultures. Fifty-six normalised variables were extracted from 14 conductive polymer sensor responses and analysed by a 3-layer back propagation neural network (NN). The NN prediction rate achieved was 98% and the test data (37.7% of all data) was recognised correctly. Successful clustering of bacterial classes was also achieved by discriminant analysis (DA) of a normalised subset of sensor data. Cross-validation identified correctly seven unknown samples. In the second series of experiments after 150 min of microaerobic growth at 37 degreesC, 24 volatile samples were collected over the headspace of H. pylori cultures in enriched (HPP) and normal (HP) media and 11 samples over sterile (N) cultures. Forty-eight sensor parameters were extracted from 12 sensor responses and analysed by a 3-layer NN previously optimised by a genetic algorithm (GA). GA-NN analysis achieved a 94% prediction rate or unknown data. Additionally the genetically selected 16 input neurones were used to perform DA-cross validation that showed a clear clustering of three groups and reclassified correctly nine sniffs. It is concluded that the most important factors that govern the performance of an intelligent bacterial odour detection system are: (a) an odour generation mechanism, (b) a rapid odour delivery system similar to the mammalian olfactory system, (c) a gas sensor array of high reproducibility and (d) a hybrid intelligent model (expert system) which will enable the parallel use of GA-NNs and multivariate techniques. (C) 1999 Elsevier Science S.A. All rights reserved.
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| 2. |
- Pavlou, AK, et al.
(författare)
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Use of an electronic nose system for diagnoses of urinary tract infections
- 2002
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Ingår i: Biosensors & bioelectronics. - : Elsevier Science B.V., Amsterdam.. - 0956-5663 .- 1873-4235. ; 17:10, s. 893-899
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Tidskriftsartikel (refereegranskat)abstract
- The use of volatile production patterns produced by bacterial contaminants in urine samples were examined using electronic nose technology. In two experiments 25 and 45 samples from patients were analysed for specific bacterial contaminants using agar culture techniques and the major UTI bacterial species identified. These samples were also analysed by incubation in a volatile generation test tube system for 4-5 h. The volatile production patterns were then analysed using an electronic nose system with 14 conducting polymer sensors. In the first experiment analysis of the data using a neural network (NN) enabled identification of all but one of the samples correctly when compared to the culture information. Four groups could be distinguished, i.e. normal urine, Escherichia coli infected, Proteus spp. and Staphylococcus spp. In the second experiment it was again possible to use NN systems to examine the volatile production patterns and identify 18 of 19 unknown UTI cases. Only one normal patient sample was mis-identified as an E coli infected sample. Discriminant function analysis also differentiated between normal urine samples, that infected with E coli and with Staphylococcus spp. This study has shown the potential for early detection of microbial contaminants in urine samples using electronic nose technology for the first time. These findings will have implications for the development of rapid systems for use in clinical practice. (C) 2002 Elsevier Science B.V. All rights reserved.
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| 3. |
- Sandström, K. J. Mattias, et al.
(författare)
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A gas-phase biosensor for environmental monitoring of formic acid: laboratory and field validation
- 2003
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Ingår i: Journal of Environmental Monitoring. - : Royal Society of Chemistry. - 1464-0325 .- 1464-0333. ; 5:3, s. 477-482
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Tidskriftsartikel (refereegranskat)abstract
- In order to encourage more exposure measurements to be performed, a formic acid gas-phase biosensor has been developed for this purpose. In the present paper, an enzyme based biosensor has been validated with respect to analyte selectivity and on-site use. To ensure that the sampler developed measures the compound of interest the biosensor was exposed to three near structural homologues to formic acid, i.e. acetic acid, methanol and formaldehyde. These vapours were generated with and without formic acid and the only compound that was found to have an effect on the performance of the biosensor, albeit a small one, was acetic acid. The field test was performed in a factory using formic acid-containing glue for glulam products. In parallel to the measurements with the biosensor a well defined reference method was used for sampling and analysing formic acid. It was found that the biosensor worked satisfactorily in this environment when used in a stationary position. It was also shown that the biosensor could determine formic acid vapour concentrations down to 0.03 mg m(-3).
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| 4. |
- Sandström, K. J. Mattias, et al.
(författare)
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Amperometric biosensor for formic acid in air
- 2000
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Ingår i: Sensors and actuators. B, Chemical. - : Elsevier. - 0925-4005 .- 1873-3077. ; 70:1–3, s. 182-187
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Tidskriftsartikel (refereegranskat)abstract
- The possibility of developing a simple, inexpensive and specific personal passive “real-time” air sampler incorporating a biosensor for formic acid was investigated. The sensor is based on the enzymatic reaction between formic acid and formate dehydrogenase (FDH) with nicotinamide adenine dinucleotide (NAD+) as a co-factor and Meldola's blue as mediator. An effective way to immobilise the enzyme, co-factor and Meldola's blue on screen-printed, disposable, electrodes was found to be in a mixture of glycerol and phosphate buffer covered with a gas-permeable membrane. Steady-state current was reached after 4–15 min and the limit of detection was calculated to be below 1 mg/m3. However, the response decreased by 50% after storage at −15°C for 1 day.
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| 5. |
- Sandström, K. J. Mattias, et al.
(författare)
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Multivariate evaluation of factors influencing the performance of a formic acid biosensor for use in air monitoring
- 2001
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Ingår i: The Analyst. - : Royal Society of Chemistry. - 0003-2654 .- 1364-5528. ; 126:11, s. 2008-2014
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Tidskriftsartikel (refereegranskat)abstract
- A formic acid biosensor for air monitoring has been evaluated using chemometric methods. Using experimental design eleven factors that could influence the performance of the biosensor were examined. The response matrices consisted of six parameters (steady state currents at three different formic acid concentrations and response rates during changes in formic acid concentrations) describing the performance of the biosensor. The data were evaluated using a combination of principal component analysis (PCA) and multiple linear regression (MLR). To confirm the conclusions from the PCA-MLR partial least squares (PLS) was also used. The most important factor for the biosensor performance was found to be the enzyme concentration. Using the information from the chemometric analyses the optimum operation conditions for the biosensor were determined. The steady state currents were increased by 18-30% and the initial two response rates increased by 47-89% compared with a biosensor that had not been optimised.
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