Determination of 24 pesticide residues in fortified wines by solid-phase microextraction and gas chromatography tandem mass spectrometry

The present work describes a solid-phase microextraction (SPME) gas chromatography_tandem mass spectrometry (MS/MS) method to quantify 24 pesticides in fortified white wine and fortified red wine. In this study “fortified wine” refers to a wine in which fermentation is arrested before completion by alcohol distillate addition, allowing sugar and alcoholic contents to be higher (around 80-100 g/L total sugars and 19-22% alcohol strength (v/v)). The analytical method showed good linearity, presenting correlation coefficients (R2) ≥ 0.989 for all compounds. Limits of detection (LOD) and quantitation (LOQ) in the ranges of 0.05-72.35 and 0.16-219.23 μg/L, respectively, were obtained. LOQs are below the maximum residue levels (MRL) set by European Regulation for grapes. The proposed method was applied to 17 commercial fortified wines. The analyzed pesticides were not detected in the wines tested.

Development of a simple analytical method for the simultaneousdetermination of paracetamol, paracetamol-glucuronide andp-aminophenol in river water

Paracetamol is among the most worldwide consumed pharmaceuticals. Although its occurrence in the environment is well documented, data about the presence of its metabolites and transformation products is very scarce. The present work describes the development of an analytical method for the simultaneous determination of paracetamol, its principal metabolite (paracetamol-glucuronide) and its main transformation product (p-aminophenol) based on solid phase extraction (SPE) and high performance liquid chromatography coupled to diode array detection (HPLC-DAD). The method was applied to analysis of river waters, showing to be suitable to be used in routine analysis. Different SPE sorbents were compared and the use of two Oasis WAX cartridges in tandem proved to be the most adequate approach for sample clean up and pre-concentration. Under optimized conditions, limits of detection in the range 40–67 ng/L were obtained, as well as mean recoveries between 60 and 110% with relative standard deviations (RSD) below 6%. Finally, the developed SPE-HPLC/DAD method was successfully applied to the analysis of the selected compounds in samples from seven rivers located in the north of Portugal. Nevertheless all the compounds were detected, it was the first time that paracetamol-glucuronide was found in river water at concentrations up to 3.57 μg/L.

Accounting for the dissociating properties of organic chemicals in LCIA: an uncertainty analysis applied to micropollutants in the assessment of freshwater ecotoxicity

In life cycle impact assessment (LCIA) models, the sorption of the ionic fraction of dissociating organic chemicals is not adequately modeled because conventional non-polar partitioning models are applied. Therefore, high uncertainties are expected when modeling the mobility, as well as the bioavailability for uptake by exposed biota and degradation, of dissociating organic chemicals. Alternative regressions that account for the ionized fraction of a molecule to estimate fate parameters were applied to the USEtox model. The most sensitive model parameters in the estimation of ecotoxicological characterization factors (CFs) of micropollutants were evaluated by Monte Carlo analysis in both the default USEtox model and the alternative approach. Negligible differences of CFs values and 95% confidence limits between the two approaches were estimated for direct emissions to the freshwater compartment; however the default USEtox model overestimates CFs and the 95% confidence limits of basic compounds up to three orders and four orders of magnitude, respectively, relatively to the alternative approach for emissions to the agricultural soil compartment. For three emission scenarios, LCIA results show that the default USEtox model overestimates freshwater ecotoxicity impacts for the emission scenarios to agricultural soil by one order of magnitude, and larger confidence limits were estimated, relatively to the alternative approach.

Optimization of QuEChERS procedure coupled to GC-ECD for organochlorine pesticide determination in carrot samples

An optimised version of the Quick, Easy, Cheap, Effective, Rugged and Safe (QuEChERS) method for simultaneous determination of 14 organochlorine pesticides in carrots was developed using gas chromatography coupled with electron-capture detector (GC-ECD) and confirmation by gas chromatography tandem mass spectrometry (GC-MS/MS). A citrate-buffered version of QuEChERS was applied for the extraction of the organochlorine pesticides, and for the extract clean-up, primary secondary amine, octadecyl-bonded silica (C18), magnesium sulphate (MgSO4) and graphitized carbon black were used as sorbents. The GC-ECD determination of the target compounds was achieved in less than 20 min. The limits of detection were below the EUmaximum residue limits (MRLs) for carrots, 10–50 μg kg−1, while the limit of quantification did exceed 10 μg kg−1 for hexachlorobenzene (HCB). The introduction of a sonication step was shown to improve the recoveries. The overall average recoveries in carrots, at the four tested levels (60, 80, 100 and 140 μg kg−1), ranged from 66 to 111% with relative standard deviations in the range of 2– 15 % (n03) for all analytes, with the exception of HCB. The method has been applied to the analysis of 21 carrot samples from different Portuguese regions, and β-HCH was the pesticide most frequently found, with concentrations oscillating between less than the limit of quantification to 14.6 μg kg−1. Only one sample had a pesticide residue (β-HCH) above the MRL, 14.6 μg kg−1. This methodology combines the advantages of both QuEChERS and GC-ECD, producing a very rapid, sensitive and reliable procedure which can be applied in routine analytical laboratories.

Dimensioning and worst-case analysis of cluster-tree sensor networks

Modeling the fundamental performance limits of Wireless Sensor Networks (WSNs) is of paramount importance to understand their behavior under the worst-case conditions and to make the appropriate design choices. This is particular relevant for time-sensitive WSN applications, where the timing behavior of the network protocols (message transmission must respect deadlines) impacts on the correct operation of these applications. In that direction this paper contributes with a methodology based on Network Calculus, which enables quick and efficient worst-case dimensioning of static or even dynamically changing cluster-tree WSNs where the data sink can either be static or mobile. We propose closed-form recurrent expressions for computing the worst-case end-to-end delays, buffering and bandwidth requirements across any source-destination path in a cluster-tree WSN. We show how to apply our methodology to the case of IEEE 802.15.4/ZigBee cluster-tree WSNs. Finally, we demonstrate the validity and analyze the accuracy of our methodology through a comprehensive experimental study using commercially available technology, namely TelosB motes running TinyOS.

On the capacity of cluster-tree ZigBee networks

Modeling the fundamental performance limits of Wireless Sensor Networks (WSNs) is of paramount importance to understand their behavior under worst-case conditions and to make the appropriate design choices. In that direction this paper contributes with an analytical methodology for modeling cluster-tree WSNs where the data sink can either be static or mobile. We assess the validity and pessimism of analytical model by comparing the worst-case results with the values measured through an experimental test-bed based on Commercial-Off- The-Shelf (COTS) technologies, namely TelosB motes running TinyOS.

Modeling and worst-case dimensioning of cluster-tree wireless sensor networks

Time-sensitive Wireless Sensor Network (WSN) applications require finite delay bounds in critical situations. This paper provides a methodology for the modeling and the worst-case dimensioning of cluster-tree WSNs. We provide a fine model of the worst-case cluster-tree topology characterized by its depth, the maximum number of child routers and the maximum number of child nodes for each parent router. Using Network Calculus, we derive “plug-and-play” expressions for the endto- end delay bounds, buffering and bandwidth requirements as a function of the WSN cluster-tree characteristics and traffic specifications. The cluster-tree topology has been adopted by many cluster-based solutions for WSNs. We demonstrate how to apply our general results for dimensioning IEEE 802.15.4/Zigbee cluster-tree WSNs. We believe that this paper shows the fundamental performance limits of cluster-tree wireless sensor networks by the provision of a simple and effective methodology for the design of such WSNs.

A comprehensive simulation study of slotted CSMA/CA for IEEE 802.15.4 wireless sensor networks

In this paper, we analyze the performance limits of the slotted CSMA/CA mechanism of IEEE 802.15.4 in the beacon-enabled mode for broadcast transmissions in WSNs. The motivation for evaluating the beacon-enabled mode is due to its flexibility for WSN applications as compared to the non-beacon enabled mode. Our analysis is based on an accurate simulation model of the slotted CSMA/CA mechanism on top of a realistic physical layer, with respect to the IEEE 802.15.4 standard specification. The performance of the slotted CSMA/CA is evaluated and analyzed for different network settings to understand the impact of the protocol attributes (superframe order, beacon order and backoff exponent) on the network performance, namely in terms of throughput (S), average delay (D) and probability of success (Ps). We introduce the concept of utility (U) as a combination of two or more metrics, to determine the best offered load range for an optimal behavior of the network. We show that the optimal network performance using slotted CSMA/CA occurs in the range of 35% to 60% with respect to an utility function proportional to the network throughput (S) divided by the average delay (D).

Application of computational intelligence to engineering

Computational Intelligence (CI) includes four main areas: Evolutionary Computation (genetic algorithms and genetic programming), Swarm Intelligence, Fuzzy Systems and Neural Networks. This article shows how CI techniques overpass the strict limits of Artificial Intelligence field and can help solving real problems from distinct engineering areas: Mechanical, Computer Science and Electrical Engineering.

SPE-LC-FD Determination of Polycyclic Aromatic Hydrocarbon Monohydroxy Derivatives in Cephalopods

A new analytical methodology, based on liquid chromatography with fluorescence detection (LC-FD), after extraction, enzymatic hydrolysis, and solid-phase extraction (SPE) through Oasis HLB cartridges, was developed and validated for the simultaneous determination of three monohydroxy derivatives of polycyclic aromatic hydrocarbons (PAHs). The optimized analytical method is sensitive, accurate, and precise, with recoveries between 62 and 110% and limits of detection of 227, 9, and 45 ng/g for 1-hydroxynaphthalene, 2-hydroxyfluorene, and 1-hydroxypyrene, respectively. Their levels were estimated in different cephalopod matrices (edible tissues and hemolymph). The methodology was applied to samples of the major cephalopod species consumed worldwide. Of the 18 samples analyzed, 39% were contaminated with 1-hydroxynaphthalene, which was the only PAH metabolite detected. Its concentration ranged from 786 to 1145 ng/g. This highly sensitive and specific method allows the identification and quantitation of PAH metabolites in forthcoming food safety and environmental monitoring programs.

Delay approximation of fractional integrals

This paper explores the calculation of fractional integrals by means of the time delay operator. The study starts by reviewing the memory properties of fractional operators and their relationship with time delay. Based on the time response of the Mittag-Leffler function an approximation of fractional integrals consisting of time delayed samples is proposed. The tuning of the approximation is optimized by means of a genetic algorithm. The results demonstrate the feasibility of the new perspective and the limits of their application.

Protein-responsive polymers for point-of-care detection of cardiac biomarker

This work describes a novel use for the polymeric film, poly(o-aminophenol) (PAP) that was made responsive to a specific protein. This was achieved through templated electropolymerization of aminophenol (AP) in the presence of protein. The procedure involved adsorbing protein on the electrode surface and thereafter electroploymerizing the aminophenol. Proteins embedded at the outer surface of the polymeric film were digested by proteinase K and then washed away thereby creating vacant sites. The capacity of the template film to specifically rebind protein was tested with myoglobin (Myo), a cardiac biomarker for ischemia. The films acted as biomimetic artificial antibodies and were produced on a gold (Au) screen printed electrode (SPE), as a step towards disposable sensors to enable point-of-care applications. Raman spectroscopy was used to follow the surface modification of the Au-SPE. The ability of the material to rebind Myo was measured by electrochemical techniques, namely electrochemical impedance spectroscopy (EIS) and square wave voltammetry (SWV). The devices displayed linear responses to Myo in EIS and SWV assays down to 4.0 and 3.5 μg/mL, respectively, with detection limits of 1.5 and 0.8 μg/mL. Good selectivity was observed in the presence of troponin T (TnT) and creatine kinase (CKMB) in SWV assays, and accurate results were obtained in applications to spiked serum. The sensor described in this work is a potential tool for screening Myo in point-of-care due to the simplicity of fabrication, disposability, short time response, low cost, good sensitivity and selectivity.

Novel biosensing device for point-of-care applications with plastic antibodies grown on Au-Screen Printed Electrodes

A gold screen printed electrode (Au-SPE) was modified by merging Molecular Imprinting and Self-Assembly Monolayer techniques for fast screening cardiac biomarkers in point-of-care (POC). For this purpose, Myoglobin (Myo) was selected as target analyte and its plastic antibody imprinted over a glutaraldehyde (Glu)/cysteamine (Cys) layer on the gold-surface. The imprinting effect was produced by growing a reticulated polymer of acrylamide (AAM) and N,N′-methylenebisacrylamide (NNMBA) around the Myo template, covalently attached to the biosensing surface. Electrochemical impedance spectroscopy (EIS) and cyclic voltammetry (CV) studies were carried out in all chemical modification steps to confirm the surface changes in the Au-SPE. The analytical features of the resulting biosensor were studied by different electrochemical techniques, including EIS, square wave voltammetry (SWV) and potentiometry. The limits of detection ranged from 0.13 to 8 μg/mL. Only potentiometry assays showed limits of detection including the cut-off Myo levels. Quantitative information was also produced for Myo concentrations ≥0.2 μg/mL. The linear response of the biosensing device showed an anionic slope of ~70 mV per decade molar concentration up to 0.3 μg/mL. The interference of coexisting species was tested and good selectivity was observed. The biosensor was successfully applied to biological fluids.

Optimizing potentiometric ionophore and electrode design for environmental on-site control of antibiotic drugs: Application to sulfamethoxazole

Potentiometric sensors are typically unable to carry out on-site monitoring of environmental drug contaminants because of their high limits of detection (LODs). Designing a novel ligand material for the target analyte and managing the composition of the internal reference solution have been the strategies employed here to produce for the first time a potentiometric-based direct reading method for an environmental drug contaminant. This concept has been applied to sulfamethoxazole (SMX), one of the many antibiotics used in aquaculture practices that may occur in environmental waters. The novel ligand has been produced by imprinting SMX on the surface of graphitic carbon nanostructures (CN) < 500 nm. The imprinted carbon nanostructures (ICN) were dispersed in plasticizer and entrapped in a PVC matrix that included (or not) a small amount of a lipophilic additive. The membrane composition was optimized on solid-contact electrodes, allowing near-Nernstian responses down to 5.2 μg/mL and detecting 1.6 μg/mL. The membranes offered good selectivity against most of the ionic compounds in environmental water. The best membrane cocktail was applied on the smaller end of a 1000 μL micropipette tip made of polypropylene. The tip was then filled with inner reference solution containing SMX and chlorate (as interfering compound). The corresponding concentrations were studied for 1 × 10−5 to 1 × 10−10 and 1 × 10−3 to 1 × 10−8 mol/L. The best condition allowed the detection of 5.92 ng/L (or 2.3 × 10−8 mol/L) SMX for a sub-Nernstian slope of −40.3 mV/decade from 5.0 × 10−8 to 2.4 × 10−5 mol/L.

Determination of Microcystin-LR in waters in the subnanomolar range by sol–gel imprinted polymers on solid contact electrodes

The present work reports new sensors for the direct determination of Microcystin-LR (MC-LR) in environmental waters. Both selective membrane and solid contact were optimized to ensure suitable analytical features in potentiometric transduction. The sensing layer consisted of Imprinted Sol–Gel (ISG) materials capable of establishing surface interactions with MC-LR. Non-Imprinted Sol–Gel (NISG) membranes were used as negative control. The effects of an ionic lipophilic additive, time of sol–gel polymerization, time of extraction of MC-LR from the sensitive layer, and pH were also studied. The solid contact was made of carbon, aluminium, titanium, copper or nickel/chromium alloys (80 : 20 or 90 : 10). The best ISG sensor had a carbon solid contact and displayed average slopes of 211.3 mV per decade, with detection limits of 7.3 1010 M, corresponding to 0.75 mg L1 . It showed linear responses in the range of 7.7 1010 to 1.9 109 M of MC-LR (corresponding to 0.77–2.00 mg L1 ), thus including the limiting value for MC-LR in waters (1.0 mg L1 ). The potentiometric-selectivity coefficients were assessed by the matched potential method for ionic species regularly found in waters up to their limiting levels. Chloride (Cl) showed limited interference while aluminium (Al3+), ammonium (NH4 + ), magnesium (Mg2+), manganese (Mn2+), sodium (Na+ ), and sulfate (SO4 2) were unable to cause the required potential change. Spiked solutions were tested with the proposed sensor. The relative errors and standard deviation obtained confirmed the accuracy and precision of the method. It also offered the advantages of low cost, portability, easy operation and suitability for adaptation to flow methods.