Sequential injection system with higher dimensional electrochemical sensor signals Part 1. Voltammetric e-tongue for the determination of oxidizable compounds

A sequential injection analysis (SIA) system was developed with the aim of obtaining an automatic and versatile way to prepare standards needed in the study of systems with higher dimensional sensor signals. To illustrate this, different analytical techniques were used in determinations of several analytes. Automated potentiometric calibrations of different potentiometric sensors, with and without interference, were carried out. Useful determinations of selectivity coefficients with two degrees of freedom were obtained. Simultaneous voltammetric determinations have also been done. Firstly, simultaneous determinations of lead and cadmium, using epoxy-graphite composite as the working electrode, have enabled a separate calibration for each metal to be obtained. Next, a voltammetric electronic tongue was designed and applied to the determination of oxidizable species. The use of artificial neural networks has solved the overlapped signal of ascorbic acid, 4-aminophenol and 4-acetamidophenol (paracetamol). A set of 63 data points was prepared automatically and has facilitated the training of an electronic tongue for these three analytes. Accurate predictions of test solutions, in the range of 12–410 μM for ascorbic acid, 17–530 μM for 4-aminophenol and 10–420 μM for paracetamol, have been achieved with RMSEs lower than 0.10 μM.     

Fluorescence optosensor using an artificial neural network for screening of polycyclic aromatic hydrocarbons

This paper presents an optosensor for screening of four polycyclic aromatic hydrocarbons: anthracene (ANT), benzo[a]pyrene (BaP), fluoranthene (FLT), and benzo[b]fluoranthene (Bbf) using a photomultiplier device with an artificial neural network as transducer. The optosensor is based on the on-line immobilization on a non-ionic resin (Amberlite XAD-4) solid support in a continuous flow. The determination was performed in 15 mM H₂PO₄⁻/HPO₄²⁻ buffer solution at pH 7 and 25% of 1,4-dioxane. Feed forward neural networks (multiplayer perceptron) have been trained to quantify the considered Polycyclic aromatic hydrocarbons (PAHs) in mixtures under optimal conditions. The optosensor proposed was also applied satisfactorily to the determination of the considered PAHs in water samples in presence of the other 12 EPA–PAHs.     

Artificial neural networks study of the catalytic reduction of resazurin: stopped-flow injection kinetic-spectrophotometric determination of Cu(II) and Ni(II)

An artificial neural network (ANN) procedure was used in the development of a catalytic spectrophotometric method for the determination of Cu(II) and Ni(II) employing a stopped-flow injection system. The method is based on the catalytic action of these ions on the reduction of resazurin by sulfide. ANNs trained by back-propagation of errors allowed us to model the systems in a concentration range of 0.5-6 and 1-15 mg l⁻¹ for Cu(II) and Ni(II), respectively, with a low relative error of prediction (REP) for each cation: REP_Cu(II) = 0.85% and REP_Ni(II) = 0.79%. The standard deviations of the repeatability (s_r) and of the within-laboratory reproducibility (s_w) were measured using standard solutions of Cu(II) and Ni(II) equal to 2.75 and 3.5 mg l⁻¹, respectively: s_r[Cu(II)] = 0.039 mg l⁻¹, s_r[Ni(II)] = 0.044 mg l⁻¹, s_w[Ni(II)] = 0.045 mg l⁻¹ and s_w[Ni(II)] = 0.050 mg l⁻¹. The ANNs-kinetic method has been applied to the determination of Cu(II) and Ni(II) in electroplating solutions and provided satisfactory results as compared with flame atomic absorption spectrophotometry method. The effect of resazurin, NaOH and Na₂S concentrations and the reaction temperature on the analytical sensitivity is discussed.     

Development of a chemical vapor sensor using piezoelectric quartz crystals with coated unusual lipids

Piezoelectric quartz crystal sensors were developed using lipids with various properties for highly sensitive detection of chemical vapors. Lipids with varying lengths of alkyl chains were coated onto 10 MHz AT-cut quartz crystal resonators and the response of these modified crystals to chemical vapors were measured. It was shown that hydrophilic compounds, such as ethanol and methanol, could be recognized efficiently by lipids having shorter alkyl chains, whereas lipids with longer alkyl chains showed affinity to more hydrophobic vapors, such as toluene, hexane and cyclohexane. Frequency changes caused by adsorption of alcohols could be enhanced when cholesterol was co-immobilized in the lipid layer. To confirm the assumption that the sensor-response might be affected by the properties of lipids derived from acyl chains, we have examined the effects of two types of newly synthesized unusual lipids on sensor response. When lipids having one triple bond each at different positions on their alkyl chains were coated onto quartz crystals separately, lower responses were observed compared to responses obtained for a sensor with immobilized, saturated phosphatidylcholine. Lipids containing -branched acyl chains, however, showed good affinity for organic vapors, and sensor responses improved 4–5-fold. Moreover, these sensors were shown to have sensitivity of the same order as the humans' sense of smell (10⁻⁵–10⁻⁶ w/w in liquid paraffin) when measured using standard odorants (isovaleric acid, skatole, etc.) for an olfactometry established in Japan.     

Artificial red cells with crosslinked hemoglobin membranes

Artificial cells containing concentrated hemoglobin (Hb) solution were prepared by interfacial polymerization of Hb with glutaraldehyde (GA) in liquid membrane capsules (LMC). A solution containing 30% of Hb was emulsified in mineral oil as red cell-size microdroplets, and this emulsion was dispersed in an aqueous phase containing glutaraldehyde to form LMC. The LMC were semipermeable templates that held the microdroplets of Hb in suspension while GA diffused through the oil to the microdroplet surfaces. The GA crosslinked Hb at the surface of each microdroplet to form an artificial red-cell membrane encapsulating Hb solution. A water-soluble surfactant was used to eject the cells from the LMC and suspend them in saline. Several surfactants were evaluated. Cell size was controlled by agitation speed during preparation of the original emulsion. Cells of 2.52 = ±1.69 μm were prepared. The encapsulated Hb retained capacity to bind and release O₂. The cells had aP ₅₀ of 8.9 torr (1200 Pa) and a capacity of 0.55 cc O₂/g of total Hb, indicating that the crosslinked portion of the Hb did not contribute to O₂ transport.     

Toward a new generation of therapeutics

Scientific evidence in the prevention and treatment of various disorders is accumulating regarding probiotics. The health benefits supported by adequate clinical data include increased resistance to infectious disease, decreased duration of diarrhea, management of inflammatory bowel disease, reduction of serum cholesterol, prevention of allergy, modulation of cytokine gene expression, and suppression of carcinogen production. Recent ventures in metabolic engineering and heterologous protein expression have enhanced the enzymatic and immunomodulatory effects of probiotics and, with time, may allow more active intervention among critical care patients. In addition, a number of approaches are currently being explored, including the physical and chemical protection of cells, to increase probiotic viability and its health benefits. Traditional immobilization of probiotics in gel matrices, most notably calcium alginate and κ-carrageenan, has frequently been employed, with noted improvements in viability during freezing and storage. Conflicting reports exist, however, on the protection offered by immobilization from harsh physiologic environments. An alternative approach, microencapsulation in “artificial cells,” builds on immobilization technologies by combining enhanced mechanical stability of the capsule membrane with improved mass transport, increased cell loading, and greater control of parameters. This review summarizes the current clinical status of probiotics, examines the promises and challenges of current immobilization technologies, and presents the concept of artificial cells for effective delivery of therapeutic bacterial cells.     

Sequential injection system with higher dimensional electrochemical sensor signals Part 2. Potentiometric e-tongue for the determination of alkaline ions

An intelligent, automatic system based on an array of non-specific-response chemical sensors was developed. As a great amount of information is required for its correct modelling, we propose a system generating it itself. The sequential injection analysis (SIA) technique was chosen as it enables the processes of training, calibration, validation and operation to be automated simply. Detection was carried out using an array of potentiometric sensors based on PVC membranes of different selectivity. The diluted standard solutions needed for system learning and response modelling are automatically prepared from more concentrated standards. The electrodes used were characterised with respect to one and two analytes, by means of high-dimensionality calibrations, and the response surface of each was represented; this characterisation enabled an interference study of great practical utility. The combined response was modelled by means of artificial neural networks (ANNs), and thus it was possible to obtain an automated electronic tongue based on SIA. In order to identify the ANN which provided the best model of the electrode responses, some of the network's parameters were optimised and its usefulness in determining NH₄⁺, K⁺ and Na⁺ ions in synthetic samples was then tested. Finally, it was used to determine these ions in commercial fertilisers, the obtained results being compared with reference methods.     

Modelling the soundscape quality of urban waterfronts by artificial neural networks

The renewal of the urban waterfronts has become a major focus of attention for politicians and decision makers in the city’s management programs. The recognition of the patterns that define the waterfronts’ identity is essential to select new strategies of intervention for the environmental recovery. In order to create adequate environments for everyday life within a sustainable development, new links between human senses, human perception and design need to be created. Within this wide approach, the landscape and the soundscape play a significant role and can become a key driving force in the implementation of the changes. New techniques have to be tested to identify the sonic and visual parameters capable to explain the specificity of a waterfront. With this purpose, an artificial neural network (ANN) was developed, and the relative importance of the input variables was evaluated. The collected database was also analysed by multiple linear regression (MLR) to compare the outcomes of both models. The urban waterfront of Naples (Italy) was chosen as case study. The results obtained show that the performance of the neural network is better than the one of the linear regression (rANN = 0.949, rMLR = 0.639). The interpretation of the relative importance method is also quite satisfactory in the ANN.     

Effective medium representation and complex modes in 3D periodic metamaterials made of cubic resonators with large permittivity at mid-infrared frequencies

We review some of the techniques that lead to the effective medium representation of a three-dimensional (3D) periodic metamaterial. We consider a 3D lattice of lead telluride cubic resonators at mid-infrared (MIR) frequencies. Each cubic resonator is modeled with both an electric and a magnetic dipole, through a method called the dual dipole approximation. The electric and magnetic polarizabilities of a cubic resonator are computed via full-wave simulations by mapping the resonator's scattered field under electric/magnetic excitation only to the field radiated by an equivalent electric/magnetic dipole. We then analyze the allowed modes in the lattice, with transverse polarization and complex wavenumber, highlighting the attenuation that each mode experiences after one free space wavelength. We observe the presence of two modes with low attenuation constant, dominant in different frequency ranges, able to propagate inside the lattice: this allows the treatment of the metamaterial as a homogeneous material with effective parameters, evaluated by using various techniques. We then show that the metamaterial under analysis allows for the generation of artificial magnetism (i.e., relative effective permeability different than unity, including negative permeability with low losses) at MIR frequencies.