One-year variation in quantity and properties of microplastics in mussels (Mytilus galloprovincialis) and cockles (Cerastoderma edule) from Aveiro lagoon.

As filter feeders, marine bivalves inhabiting estuarine and coastal areas are directly exposed to microplastics (MPs) in water. To assess whether MPs number, and their shape, size, colour, and polymer type present in mussels (Mytilus galloprovincialis) and cockles (Cerastoderma edule) varied over one year, bivalves were collected over the year of 2019 in the lower part of the coastal Aveiro lagoon, Portugal. After extraction from the bivalve's whole-body soft tissues, a subset of the visually inspected particles was randomly separated for identification using the Fourier-transform mid-infrared (FT-MIR) spectroscopy. A fraction of the inspected particles, 26-32% of particles >100 µm, and 59-100% of smaller ones were confirmed as MPs. Concentrations varied within the intervals of 0.77-4.3 items g-1 in mussels and 0.83-5.1 items g-1 in cockles, with the lowest values observed in January. In winter, the accumulation of large-sized fibers was composed of a mixture of plastic types, which contrasted against the most abundant MPs in summer consisting mainly of polyethylene of diverse size classes and shapes. Temperature decrease registered in winter might have triggered a lower filtration rate, resulting in lower MPs concentrations in the whole-soft body tissues of organisms. Different properties of MPs found in bivalves between January-February and August-September appear to reflect changes in the characteristics of MPs available in the Aveiro lagoon.

Urinary metabolomic profiling of asthmatics can be related to clinical characteristics.

Metabolomics has been increasingly explored to achieve an improved understanding of asthma. In the current observational and exploratory study, the first to have examined the relationship between oxidative stress extension, eosinophilic inflammation, and disease severity in asthmatic patients, metabolomics (using target aliphatic aldehydes and alkanes) was carried out using solid-phase microextraction (SPME) followed by a comprehensive two-dimensional gas chromatography coupled to mass spectrometry with a high-resolution time-of-flight analyzer (GC×GC-ToFMS). We were able to demonstrate that metabolomics can give valuable insights into asthma mechanisms once lipidic peroxidation assessed by urinary metabolomics is related to the clinical characteristics of nonobese asthmatics, such as disease severity, lung function, and eosinophilic inflammation. Nevertheless, considering our sample size, the obtained results require further validation using a much larger sample cohort.

Detection of copper, lead, cadmium and iron in wine using electronic tongue sensor system.

An array of 10 potentiometric chemical sensors has been applied to the detection of total Fe, Cu, Pb and Cd content in digested wine. As digestion of organic matter of wine is necessary prior to the trace metal detection using potentiometric sensors, sample preparation procedures have been optimized. Different variants of wet and microwave digestion and dry ashing, 14 conditions in total, have been tested. Decomposition of organic matter was assessed using Fourier transform mid-infrared spectroscopy and total phenolic content. Dry ashing was found to be the most effective method of wine digestion. Measurements with sensors in individual solutions of Fe(III), Cu(II), Pb(II) and Cd(II) prepared on different backgrounds have shown that their detection limits were below typical concentration levels of these metals in wines and, in the case of Cu, Pb and Cd below maximum allowed concentrations. Detection of Fe in digested wine samples was possible using discrete iron-sensitive sensors with chalcogenide glass membranes with RMSEP of 0.05 mmol L(-1) in the concentration range from 0.0786 to 0.472 mmol L(-1). Low concentration levels of Cu, Pb and Cd in wine and cross-sensitivity of respective sensors resulted in the non-linearity of their responses, requiring back-propagation neural network for the calibration. Calibration models have been calculated using measurements in the model mixed solutions containing all three metals and a set of digested wine sample. RMSEP values for Cu, Pb and Cd were 3.9, 39 and 1.2 µmol L(-1) in model solutions and 2, 150 and 1 µmol L(-1) in digested wine samples.

Design of molecularly imprinted polymers for diphenylamine sensing.

A series of the polymers imprinted with diphenylamine (DPA) and respective non imprinted polymers were synthesized using precipitation polymerization. Synthesized polymers were characterized by Fourier Transform Infra-Red spectroscopy with Total Attenuated Reflectance (FTIR-ATR), Scanning Electron Microscopy (SEM) and equilibrium batch re-binding experiments. Influence of the synthesis conditions, namely monomer/template ratio and reaction duration, on the polymer binding capacity and selectivity towards aromatic compounds was investigated. Binding behavior of MIP was described using Freundlich isotherm. Significance of the effects of the synthesis conditions on the polymer properties was evaluated using ANOVA. MIPs synthesized at different conditions, which displayed different properties (binding capacity and selectivity), and respective non-imprinted polymers were employed for the fabrication of the potentiometric sensors. While sensors prepared using imprinted polymers had higher sensitivity and selectivity compared to the ones containing non-imprinted polymer, no difference was observed between sensors containing different imprinted polymers. No correspondence between polymers' characteristics obtained in the equilibrium re-binding studies and potentiometric behavior of the sensors based on the same polymers was observed. Therefore, equilibrium re-binding studies cannot be used for predicting sensor behavior.

Evaluation of the feasibility of the electronic tongue as a rapid analytical tool for wine age prediction and quantification of the organic acids and phenolic compounds. The case-study of Madeira wine.

A set of fourteen Madeira wines comprising wines produced from four Vitis vinifera L. varieties (Bual, Malvasia, Verdelho and Tinta Negra Mole) that were 3, 6, 10 and 17 years old was analysed using HPLC and an electronic tongue (ET) multisensor system. Concentrations of 24 organic acids, phenolic and furanic compounds were determined by HPLC. The ET consisting of 26 potentiometric chemical sensors with plasticized PVC and chalcogenide glass membranes was used. Significance of the effects of age and variety on the ET response and wine composition with respect to the organic acids, phenolics and furanic derivatives were evaluated using ANOVA-Simultaneous Component Analysis (ASCA). Significance of the effects was estimated using a permutation test (1000 permutations). It was found that effects of age, grape variety and their interaction were significant for the HPLC data set and only the effect of age was significant for the ET data. Calibration models of the HPLC and ET data with respect to the wine age and of the ET data with respect to the concentration of the organic acids and phenolics were calculated using PLS1 regression. Models were validated using cross-validation. It was possible to predict wine age from HPLC and ET data with the accuracy in cross-validation of 2.6 and 1.8 years respectively. The ET was capable of detecting the following components (mean relative error in cross-validation is shown in the parentheses): tartaric (8%), citric (5%), formic (12%), protocatehuic (5%), vanillic (18%) and sinapic (14%) acids, catechin (6%), vanillin (12%) and trans-resveratrol (5%). The ET capability of predicting Madeira wine age with good accuracy (1.8 years) as well as quantify of some organic acids and phenolic compounds was demonstrated.

Study of the influence of micro-oxygenation and oak chip maceration on wine composition using an electronic tongue and chemical analysis.

The influence of micro-oxygenation (MOX) and maceration with oak chips treatments on wine was studied on wine samples from three vintages produced in the Yarra Valley, Australia. A full factorial design was employed where two factors (MOX and oak chips treatments) had two levels and one factor (vintage) had three levels. Three replicated treatments were run for each factor's setting. Wine samples were analysed using conventional laboratory methods with respect to the phenolic wine compounds and colour attributes since the phenolic fraction of wine is most affected by both MOX and oak maceration treatments. The same wine samples were measured with an electronic tongue based on potentiometric chemical sensors. The significance of treatments and vintage effects on wine phenolic compounds was assessed using ANOVA and ANOVA-Simultaneous Component Analysis (ASCA). Cross-validation was used for the ASCA sub-model optimisations and permutation test for evaluations of the significance of the factors. Main effects of vintage and maceration with oak chips were found to be significant for both physicochemical and the ET data. Main effect of MOX treatment was also found significant for the physicochemical parameters. The largest effect on the phenolic composition of wine was due to its vintage, which accounted for 70% and 33% of total variance in the physicochemical and ET data respectively. The ET was calibrated with respect to the total phenolic content, colour density and hue and chemical ages 1 and 2 and could predict these parameters of wine with good precision.

Differentiation of four Aspergillus species and one Zygosaccharomyces with two electronic tongues based on different measurement techniques.

Two electronic tongues based on different measurement techniques were applied to the discrimination of four molds and one yeast. Chosen microorganisms were different species of Aspergillus and yeast specie Zygosaccharomyces bailii, which are known as food contaminants. The electronic tongue developed in Linköping University was based on voltammetry. Four working electrodes made of noble metals were used in a standard three-electrode configuration in this case. The St. Petersburg electronic tongue consisted of 27 potentiometric chemical sensors with enhanced cross-sensitivity. Sensors with chalcogenide glass and plasticized PVC membranes were used. Two sets of samples were measured using both electronic tongues. Firstly, broths were measured in which either one of the molds or the yeast grew until late logarithmic phase or border of the stationary phase. Broths inoculated by either one of molds or the yeast was measured at five different times during microorganism growth. Data were evaluated using principal component analysis (PCA), partial least square regression (PLS) and linear discriminant analysis (LDA). It was found that both measurement techniques could differentiate between fungi species. Merged data from both electronic tongues improved differentiation of the samples in selected cases.

Multicomponent analysis of fermentation growth media using the electronic tongue (ET).

A potentiometric electronic tongue (ET) consisting of eight cross-sensitive chemical sensors and a standard pH electrode has been applied for analysis of simulated fermentation solutions typical for fermentation processes with Aspergillus niger. The electronic tongue has been found capable of simultaneous determination of ammonium, citrate and oxalate in complex media with good precision (typical error within 8%). The system preserved high sensitivity to the targeted substances also in the presence of sodium azide, which is commonly used for suppressing microbial activity in real-world fermentation samples. Sensor performance was fast and reproducible which promises well for routine application of the electronic tongue for fermentation process monitoring.

Multisensor system on the basis of an array of non-specific chemical sensors and artificial neural networks for determination of inorganic pollutants in a model groundwater.

The application of a multisensor system to groundwater monitoring is investigated. The sensor system is based on an array of non-specific potentiometric chemical sensors with data processing by artificial neural networks and includes 13 sensors with PVC membranes and 12 solid-state ones. Results of measurements in model solutions containing heavy metals, alkali- and alkali-earth cations and inorganic anions at concentrations typical for groundwater near the city of Braunschweig, Germany, are presented. Both the response of the whole sensor array and the responses of subsystems consisting only of PVC and only of solid-state sensors, respectively, are investigated. It is shown that both subsystems can be used for determination of described ions and that the best results are obtained if the whole array of sensors is used.