Fractionation of a hydrocolloid emulsifier reclaimed from winery waste.

Complex hydrocolloids have been isolated and fractionated using a consecutive elution process, starting from winery waste. These extracts consist mainly of polysaccharidic populations and of smaller protein molecules and they exhibit emulsifying, thickening and texture-modifying activity. This work is a systematic study of these individual populations, as fractionated with preparative size exclusion chromatography (Prep-SEC) in terms of their chemical identity, surface properties, and emulsification behavior. The fractions have been characterized via SEC-MALLS, FTIR, DLS, zeta potential, and interfacial tension measurements. The results highlight the antagonistic and synergistic effects of the individual components of the above-mentioned complex natural material (winery waste extract) towards its emulsifying behavior, and provide a model for the kinetics of the evolution of a Pickering interfacial layer.

Detection of Mycobacterium tuberculosis (TB) in vitro and in situ using an electronic nose in combination with a neural network system.

The use of volatile production patterns produced by Mycobacterium tuberculosis and associated bacterial infections from sputum samples were examined in vitro and in situ using an electronic nose based on a 14 sensor conducting polymer array. In vitro, it was possible to successfully discriminate between M. tuberculosis (TB) and control media, and between M. tuberculosis and M. avium, M. scrofulaceum and Pseudomonas aeruginosa cultures in the stationary phase after 5-6h incubation at 37 degrees C based on 35 samples. Using neural network (NN) analysis and cross-validation it was possible to successfully identify 100% of the TB cultures from others. A second in vitro study with 61 samples all four groups were successfully discriminated with 14 of 15 unknowns within each of the four groups successfully identified using cross-validation and discriminant function analysis. Subsequently, lipase enzymes were added to 46 sputum samples directly obtained from patients and the head space analysed. Parallel measurements of bacterial contamination were also carried out for confirmation using agar media. NN analysis was carried out using some of the samples as a training set. Based on the NN and genetic algorithms of up to 10 generations it was possible to successfully cross-validate 9 of 10 unknown samples. PCA was able to discriminate between TB infection alone, the controls, M. avium, P. aeruginosa and a mixed infection. These findings will have significant implications for the development of rapid qualitative systems for screening of patient samples and clinical diagnosis of tuberculosis.

Use of an electronic nose system for diagnoses of urinary tract infections.

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.