Feature selection for chemical sensor arrays using mutual information

We address the problem of feature selection for classifying a diverse set of chemicals using an array of metal oxide sensors. Our aim is to evaluate a filter approach to feature selection with reference to previous work, which used a wrapper approach on the same data set, and established best features and upper bounds on classification performance. We selected feature sets that exhibit the maximal mutual information with the identity of the chemicals. The selected features closely match those found to perform well in the previous study using a wrapper approach to conduct an exhaustive search of all permitted feature combinations. By comparing the classification performance of support vector machines (using features selected by mutual information) with the performance observed in the previous study, we found that while our approach does not always give the maximum possible classification performance, it always selects features that achieve classification performance approaching the optimum obtained by exhaustive search. We performed further classification using the selected feature set with some common classifiers and found that, for the selected features, Bayesian Networks gave the best performance. Finally, we compared the observed classification performances with the performance of classifiers using randomly selected features. We found that the selected features consistently outperformed randomly selected features for all tested classifiers. The mutual information filter approach is therefore a computationally efficient method for selecting near optimal features for chemical sensor arrays

Bio-Benchmarking of Electronic Nose Sensors

BACKGROUND:Electronic noses, E-Noses, are instruments designed to reproduce the performance of animal noses or antennae but generally they cannot match the discriminating power of the biological original and have, therefore, been of limited utility. The manner in which odorant space is sampled is a critical factor in the performance of all noses but so far it has been described in detail only for the fly antenna. METHODOLOGY:Here we describe how a set of metal oxide (MOx) E-Nose sensors, which is the most commonly used type, samples odorant space and compare it with what is known about fly odorant receptors (ORs). PRINCIPAL FINDINGS:Compared with a fly's odorant receptors, MOx sensors from an electronic nose are on average more narrowly tuned but much more highly correlated with each other. A set of insect ORs can therefore sample broader regions of odorant space independently and redundantly than an equivalent number of MOx sensors. The comparison also highlights some important questions about the molecular nature of fly ORs. CONCLUSIONS:The comparative approach generates practical learnings that may be taken up by solid-state physicists or engineers in designing new solid-state electronic nose sensors. It also potentially deepens our understanding of the performance of the biological system

Clinicopathologic features of incidental prostatic adenocarcinoma in radical cystoprostatectomy specimens

<p>Abstract</p> <p>Background</p> <p>The aim of this study is to review all features of incidentally discovered prostate adenocarcinoma in patients undergoing radical cystoprostatectomy for bladder cancer.</p> <p>Methods</p> <p>The medical charts of 300 male patients who underwent radical cystoprostatectomy for bladder cancer between 1997 and 2005 were retrospectively reviewed. The mean age of the patients was 62 (range 51-75) years.</p> <p>Results</p> <p>Prostate adenocarcinoma was present in 60 (20%) of 300 specimens. All were acinar adenocarcinoma. Of these, 40 (66.7%) were located in peripheral zone, 20 (33.3%) had pT2a tumor, 12 (20%) had pT2b tumor, 22(36.7%) had pT2c and, 6 (10%) had pT3a tumor. Gleason score was 6 or less in 48 (80%) patients. Surgical margins were negative in 54 (90%) patients, and tumor volume was less than 0.5 cc in 23 (38.3%) patients. Of the 60 incidentally detected cases of prostate adenocarcinoma 40 (66.7%) were considered clinically significant.</p> <p>Conclusion</p> <p>Incidentally detected prostate adenocarcinoma is frequently observed in radical cystoprostatectomy specimens. The majority are clinically significant.</p

Long-term postharvest aroma evolution of tomatoes with the alcobaça (alc) mutation

The postharvest evolution of Penjar tomatoes has been studied in four accessions representative of the variability of the varietal type. The long-term shelf life of these materials, which carry the alc allele, was confirmed with 31.2-59.1% of commercial fruits after 6 months of effective conservation at room temperature and a limited loss of weight (21.1-27.9%). Aroma in Penjar tomatoes is differentiated from other tomato varieties by a characteristic 'sharp-floral' aroma descriptor. The evolution of the 'sharp-floral' aroma during postharvest showed a peak of intensity at 2 months of postharvest, though in one accession a delay of 2 months in this response was detected. Out of 25 volatiles analysed, including main and background notes, a reverse iPLS variable selection revealed that the main candidates behind this aromatic behaviour are ¿-terpineol, trans-2-hexenal, 6-methyl-5-hepten-2-one, trans-2-octenal, ¿-pinene, ß-ionone, 2 + 3-methylbutanol and phenylacetaldehyde. Between harvest and 2 months postharvest, most compounds reduced considerably their concentration, while the intensity of the 'sharp-floral' descriptor increased, which means that probably there is a rearrangement of the relative concentrations among volatiles that may lead to masking/unmasking processes. © 2011 Springer-Verlag.This work was supported by grants from the Conselleria de Agricultura, Pesca y Alimentacio de la Comunidad Valenciana, the Fundacion de la Comunidad Valenciana para la Investigacion Agroalimentaria (AGROALIMED) and from the Departament d'Agricultura, Alimentacio i Accio Rural (DAR) de la Generalitat de Catalunya.Casals Missio, J.; Cebolla Cornejo, J.; Rosello Ripolles, S.; Beltran Arandes, J.; Casanas, F.; Nuez Viñals, F. (2011). Long-term postharvest aroma evolution of tomatoes with the alcobaça (alc) mutation. 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Quality Coding by Neural Populations in the Early Olfactory Pathway: Analysis Using Information Theory and Lessons for Artificial Olfactory Systems

In this article, we analyze the ability of the early olfactory system to detect and discriminate different odors by means of information theory measurements applied to olfactory bulb activity images. We have studied the role that the diversity and number of receptor neuron types play in encoding chemical information. Our results show that the olfactory receptors of the biological system are low correlated and present good coverage of the input space. The coding capacity of ensembles of olfactory receptors with the same receptive range is maximized when the receptors cover half of the odor input space - a configuration that corresponds to receptors that are not particularly selective. However, the ensemble’s performance slightly increases when mixing uncorrelated receptors of different receptive ranges. Our results confirm that the low correlation between sensors could be more significant than the sensor selectivity for general purpose chemo-sensory systems, whether these are biological or biomimetic

Comparison of the performance of metal oxide and conducting polymer electronic noses for detection of aflatoxin using artificially contaminated maize

The electronic nose offers potential as a rapid and cost effective field portable diagnostic device that would allow for quick screening of produce for aflatoxin contamination at the market entry level. This study aimed to compare the performance of three electronic nose sensor technologies: metal oxide semiconductor sensors (Fox 3000), conducting polymer sensors (Cyranose 320) and doped metal oxide semiconductor sensors with thermocycling (DiagNose), for the detection of volatiles associated with maize contaminated with aflatoxins. Australian maize (variety DK703w) samples were artificially inoculated with aflatoxigenic and non-aflatoxigenic Aspergillus flavus isolates and 2 % v/v Tween 20 as a control. Mutual information was used to select features from the electronic nose sensor signals for classification of the samples. The effectiveness, of selected features to discriminate between the different classes of samples was evaluated by support vector machines and k-nearest neighbour with leave-one-out cross-validation. Cross-validated classification accuracy for the different sample classes ranged from 81 % to 94 % for DiagNose, 76 to 79 % for Fox 3000 and 68 to 75 % for Cyranose. The results suggest that an electronic nose equipped with doped metal oxide semiconductor sensors and thermocycling is more effective for detection of aflatoxin contamination of maize