Exploiting Evolution for an Adaptive Drift-Robust Classifier in Chemical Sensing

Gas chemical sensors are strongly affected by drift, i.e., changes in sensors' response with time, that may turn statistical models commonly used for classification completely useless after a period of time. This paper presents a new classifier that embeds an adaptive stage able to reduce drift effects. The proposed system exploits a state-of-the-art evolutionary strategy to iteratively tweak the coefficients of a linear transformation able to transparently transform raw measures in order to mitigate the negative effects of the drift. The system operates continuously. The optimal correction strategy is learnt without a-priori models or other hypothesis on the behavior of physical-chemical sensors. Experimental results demonstrate the efficacy of the approach on a real problem

Increasing pattern recognition accuracy for chemical sensing by evolutionary based drift compensation

Artificial olfaction systems, which mimic human olfaction by using arrays of gas chemical sensors combined with pattern recognition methods, represent a potentially low-cost tool in many areas of industry such as perfumery, food and drink production, clinical diagnosis, health and safety, environmental monitoring and process control. However, successful applications of these systems are still largely limited to specialized laboratories. Sensor drift, i.e., the lack of a sensor's stability over time, still limits real in dustrial setups. This paper presents and discusses an evolutionary based adaptive drift-correction method designed to work with state-of-the-art classification systems. The proposed approach exploits a cutting-edge evolutionary strategy to iteratively tweak the coefficients of a linear transformation which can transparently correct raw sensors' measures thus mitigating the negative effects of the drift. The method learns the optimal correction strategy without the use of models or other hypotheses on the behavior of the physical chemical sensors

Uptake and transport of novel amphiphilic polyelectrolyte-insulin nanocomplexes by caco-2 cells - towards oral insulin

“The original publication is available at www.springerlink.com”. Copyright SpringerPurpose: The influence of polymer architecture on cellular uptake and transport across Caco-2 cells of novel amphiphilic polyelectrolyte-insulin nanocomplexes was investigated. Method: Polyallylamine (PAA) (15 kDa) was grafted with palmitoyl chains (Pa) and subsequently modified with quaternary ammonium moieties (QPa). These two amphiphilic polyelectrolytes (APs) were tagged with rhodamine and their uptake by Caco-2 cells or their polyelectrolyte complexes (PECs) with fluorescein isothiocyanate-insulin (FITC-insulin) uptake were investigated using fluorescence microscopy. The integrity of the monolayer was determined by measurement of transepithelial electrical resistance (TEER). Insulin transport through Caco-2 monolayers was determined during TEER experiments. Result: Pa and insulin were co-localised in the cell membranes while QPa complexes were found within the cytoplasm. QPa complex uptake was not affected by calcium, cytochalasin D or nocodazole. Uptake was reduced by co-incubation with sodium azide, an active transport inhibitor. Both polymers opened tight junctions reversibly where the TEER values fell by up to 35 % within 30 minutes incubation with Caco-2 cells. Insulin transport through monolayers increased when QPa was used (0.27 ngmL-1 of insulin in basal compartment) compared to Pa (0.14 ngmL-1 of insulin in basal compartment) after 2 hours. Conclusion: These APs have been shown to be taken up by Caco-2 cells and reversibly open tight cell junctions. Further work is required to optimise these formulations with a view to maximising their potential to facilitate oral delivery of insulin.Peer reviewe

Prevalence of Anaplasma phagocytophilum infection and effect on lamb growth

Background: A major challenge in sheep farming during the grazing season along the coast of south-western Norway is tick-borne fever (TBF) caused by the bacteria Anaplasma phagocytophilum that is transmitted by the tick Ixodes ricinus. Methods: A study was carried out in 2007 and 2008 to examine the prevalence of A. phagocytophilum infection and effect on weaning weight in lambs. The study included 1208 lambs from farms in Sunndal Ram Circle in Møre and Romsdal County in Mid-Norway, where ticks are frequently observed. All lambs were blood sampled and serum was analyzed by an indirect fluorescent antibody assay (IFA) to determine an antibody status (positive or negative) to A. phagocytophilum infection. Weight and weight gain and possible effect of infection were analyzed using ANOVA and the MIXED procedure in SAS. Results: The overall prevalence of infection with A. phagocytophilum was 55%. A lower weaning weight of 3% (1.34 kg, p < 0.01) was estimated in lambs seropositive to an A. phagocytophilum infection compared to seronegative lambs at an average age of 137 days. Conclusions: The results show that A. phagocytophilum infection has an effect on lamb weight gain. The study also support previous findings that A. phagocytophilum infection is widespread in areas where ticks are prevalent, even in flocks treated prophylactic with acaricides

Chitosan encapsulation modulates the effect of capsaicin on the tight junctions of MDCK cells

Capsaicin has known pharmacological effects including the ability to reversibly open cellular tight junctions, among others. The aim of this study was to develop a strategy to enhance the paracellular transport of a substance with low permeability (FITC-dextran) across an epithelial cell monolayer via reversible opening of cellular tight junctions using a nanosystem comprised by capsaicin and of chitosan. We compared the biophysical properties of free capsaicin and capsaicin-loaded chitosan nanocapsules, including their cytotoxicity towards epithelial MDCK-C7 cells and their effect on the integrity of tight junctions, membrane permeability and cellular uptake. The cytotoxic response of MDCK-C7 cells to capsaicin at a concentration of 500 μM, which was evident for the free compound, is not observable following its encapsulation. The interaction between nanocapsules and the tight junctions of MDCK-C7 cells was investigated by impedance spectroscopy, digital holographic microscopy and structured illumination fluorescence microscopy. The nanocapsules modulated the interaction between capsaicin and tight junctions as shown by the different time profile of trans-epithelial electrical resistance and the enhanced permeability of monolayers incubated with FITC-dextran. Structured illumination fluorescence microscopy showed that the nanocapsules were internalized by MDCK-C7 cells. The capsaicin-loaded nanocapsules could be further developed as drug nanocarriers with enhanced epithelial permeability

Intelligent Bayes Classifier (IBC) for ENT infection classification in hospital environment

Electronic Nose based ENT bacteria identification in hospital environment is a classical and challenging problem of classification. In this paper an electronic nose (e-nose), comprising a hybrid array of 12 tin oxide sensors (SnO(2)) and 6 conducting polymer sensors has been used to identify three species of bacteria, Escherichia coli (E. coli), Staphylococcus aureus (S. aureus), and Pseudomonas aeruginosa (P. aeruginosa) responsible for ear nose and throat (ENT) infections when collected as swab sample from infected patients and kept in ISO agar solution in the hospital environment. In the next stage a sub-classification technique has been developed for the classification of two different species of S. aureus, namely Methicillin-Resistant S. aureus (MRSA) and Methicillin Susceptible S. aureus (MSSA). An innovative Intelligent Bayes Classifier (IBC) based on "Baye's theorem" and "maximum probability rule" was developed and investigated for these three main groups of ENT bacteria. Along with the IBC three other supervised classifiers (namely, Multilayer Perceptron (MLP), Probabilistic neural network (PNN), and Radial Basis Function Network (RBFN)) were used to classify the three main bacteria classes. A comparative evaluation of the classifiers was conducted for this application. IBC outperformed MLP, PNN and RBFN. The best results suggest that we are able to identify and classify three bacteria main classes with up to 100% accuracy rate using IBC. We have also achieved 100% classification accuracy for the classification of MRSA and MSSA samples with IBC. We can conclude that this study proves that IBC based e-nose can provide very strong and rapid solution for the identification of ENT infections in hospital environment

The value of selected in vitro and in silico methods to predict acute oral toxicity in a regulatory context: results from the European Project ACuteTox

ACuteTox is a project within the 6th European Framework Programme which had as one of its goals to develop, optimise and prevalidate a non-animal testing strategy for predicting human acute oral toxicity. In its last 6months, a challenging exercise was conducted to assess the predictive capacity of the developed testing strategies and final identification of the most promising ones. Thirty-two chemicals were tested blind in the battery of in vitro and in silico methods selected during the first phase of the project. This paper describes the classification approaches studied: single step procedures and two step tiered testing strategies. In summary, four in vitro testing strategies were proposed as best performing in terms of predictive capacity with respect to the European acute oral toxicity classification. In addition, a heuristic testing strategy is suggested that combines the prediction results gained from the neutral red uptake assay performed in 3T3 cells, with information on neurotoxicity alerts identified by the primary rat brain aggregates test method. Octanol-water partition coefficients and in silico prediction of intestinal absorption and blood-brain barrier passage are also considered. This approach allows to reduce the number of chemicals wrongly predicted as not classified (LD(50)>2000mg/kg b.w.).Peer Reviewe

Modeling the pharmacodynamics of passive membrane permeability

Small molecule permeability through cellular membranes is critical to a better understanding of pharmacodynamics and the drug discovery endeavor. Such permeability may be estimated as a function of the free energy change of barrier crossing by invoking the barrier domain model, which posits that permeation is limited by passage through a single “barrier domain” and assumes diffusivity differences among compounds of similar structure are negligible. Inspired by the work of Rezai and co-workers (JACS 128:14073–14080, 2006), we estimate this free energy change as the difference in implicit solvation free energies in chloroform and water, but extend their model to include solute conformational affects. Using a set of eleven structurally diverse FDA approved compounds and a set of thirteen congeneric molecules, we show that the solvation free energies are dominated by the global minima, which allows solute conformational distributions to be effectively neglected. For the set of tested compounds, the best correlation with experiment is obtained when the implicit chloroform global minimum is used to evaluate the solvation free energy difference

Thiolated chitosan nanoparticles enhance anti-inflammatory effects of intranasally delivered theophylline

BACKGROUND: Chitosan, a polymer derived from chitin, has been used for nasal drug delivery because of its biocompatibility, biodegradability and bioadhesiveness. Theophylline is a drug that reduces the inflammatory effects of allergic asthma but is difficult to administer at an appropriate dosage without causing adverse side effects. It was hypothesized that adsorption of theophylline to chitosan nanoparticles modified by the addition of thiol groups would improve theophylline absorption by the bronchial epithelium and enhance its anti-inflammatory effects. OBJECTIVES: We sought to develop an improved drug-delivery matrix for theophylline based on thiolated chitosan, and to investigate whether thiolated chitosan nanoparticles (TCNs) can enhance theophylline's capacity to alleviate allergic asthma. METHODS: A mouse model of allergic asthma was used to test the effects of theophylline in vivo. BALB/c mice were sensitized to ovalbumin (OVA) and OVA-challenged to produce an inflammatory allergic condition. They were then treated intranasally with theophylline alone, chitosan nanoparticles alone or theophylline adsorbed to TCNs. The effects of theophylline on cellular infiltration in bronchoalveolar lavage (BAL) fluid, histopathology of lung sections, and apoptosis of lung cells were investigated to determine the effectiveness of TCNs as a drug-delivery vehicle for theophylline. RESULTS: Theophylline alone exerts a moderate anti-inflammatory effect, as evidenced by the decrease in eosinophils in BAL fluid, the reduction of bronchial damage, inhibition of mucus hypersecretion and increased apoptosis of lung cells. The effects of theophylline were significantly enhanced when the drug was delivered by TCNs. CONCLUSION: Intranasal delivery of theophylline complexed with TCNs augmented the anti-inflammatory effects of the drug compared to theophylline administered alone in a mouse model of allergic asthma. The beneficial effects of theophylline in treating asthma may be enhanced through the use of this novel drug delivery system