A highly-sensitive glucose biosensor amenable to ultra-miniaturisation was fabricated by immobilisation of glucose oxidase (GOx), onto a poly(2,6-diaminopyridine)/multi-walled carbon nanotube/glassy carbon electrode (poly(2,6-DP)/MWNT/GCE). Cyclic voltammetry was used for both the electrochemical synthesis of poly-(2,6-DP) on the surface of a MWNT-modified GC electrode, and characterisation of the polymers deposited on the GC electrode. The synergistic effect of the high active surface area of both the conducting polymer, i.e., poly-(2,6-DP) and MWNT gave rise to a remarkable improvement in the electrocatalytic properties of the biosensor. The transfer coefficient (alpha), heterogeneous electron transfer rate constant and Michaelis-Menten constant were calculated to be 0.6, 4 s(-1) and 0.20 mM at pH 7.4, respectively. The GOx/poly(2,6-DP)/MWNT/GC bioelectrode exhibited two linear responses to glucose in the concentration ranging from 0.42 mu M to 8.0 mM with a correlation coefficient of 0.95, sensitivity of 52.0 mu AmM-1 cm(-2), repeatability of 1.6% and long-term stability, which could make it a promising bioelectrode for precise detection of glucose in the biological samples. (C) 2013 Elsevier B.V. All rights reserved.

A highly-sensitive glucose biosensor amenable to ultraminiaturisation was fabricated by immobilization of glucose oxidase (wGOX), onto a poly(2,6-diaminopyridine)/multi-walled carbon nanotube/glassy carbon electrode (poly(2,6-DP)/MWCNT/GCE). Cyclic voltammetry was used for both the electrochemical synthesis of poly-(2,6-DP) on the surface of a MWCNT-modified GC electrode, and characterization of the polymers deposited on the GC electrode. The synergistic effect of the high active surface area of both the conducting-polymer, i.e., poly-(2,6-DP) and MWCNT gave rise to a remarkable improvement in the electrocatalytic properties of the biosensor. The transfer coefficient (alpha), heterogeneous electron transfer rate constant and Michaelis-Menten constant were calculated to be 0.6, 4 s-1 and 0.22 mM at pH 7.4, respectively. The GOx/poly(2,6-DP)/MWCNT/GC bioelectrode exhibited two linear responses to glucose in the concentration ranging from 0.42 mu M to 8.0 mM with a correlation coefficient of 0.95, sensitivity of 52.0 mu AmM-1 cm-2, repeatability of 1.6% and long-term stability, which could make it a promising bioelectrode for precise detection of glucose in the biological samples. (C) 2016 Elsevier B.V. All rights reserved.

This paper describes the electrochemical characterisation of a range of gold and platinum microelectrode arrays (MEAs) fabricated by standardphotolithographic methods. The inter-electrode spacing, geometry, numbers and dimensions of the electrodes in the arrays were found to influencethe voltammetric behaviours obtained. Excellent correlation was found between experimental data and theoretical predictions employing publishedmodels of microelectrode behaviour. Gold MEAs were evaluated for their applicability to copper determination in a soil extract sample, whereagreement was found between the standard analytical method and a method based on underpotential deposition—anodic stripping voltammetry(UPD-ASV) at the MEAs, offering a mercury-free alternative for copper sensing.

A sensor employing pulse voltammetry monitored the liquid phase of a biogas reactor during 32 days of gas production An electrode allay consisting of stainless steel, platinum and rhodium electrodes generated current responses for a sequence of voltage pulses Plots of individual current responses against time indicated the electrochemical changes occurring in the broth from the perspective of each electrode. The responses from stainless steel had a pronounced diurnal oscillation which followed the daily introduction and consumption of substrate The current responses for platinum were in a narrow range whereas those for rhodium exhibited several minima A disturbance in the reactor caused by omission of substrate led to decreases in both gas production and current responses for all the electrodes Multivariate data evaluation of all the current responses by principal component analysis indicated the daily fluctuations for concentrations of ions and redox active compounds in the broth

Global glycosylation changes of serum proteins in type 1 diabetic patients have in this paper been investigated based on the interaction of the saccharide moiety of serum proteins with different lectins. Lectins are proteins, which bind carbohydrates specifically and reversibly. Panels with lectins of various carbohydrate specificities were immobilized on gold surfaces. Sera from healthy individuals, newly diagnosed type 1 diabetes patients and type 1 diabetes patients having had the disease for 4–6 years, respectively, were applied to the lectin panel. The biorecognition was evaluated with null ellipsometry. Data obtained were related to an internal standard of lactoferrin. Multivariate data analysis (MVDA) techniques were used to analyze data.

Principal component analysis showed that the lectin panel enabled discrimination between sera from the three different above-mentioned groups. Using an artificial neuronal net (ANN), it was possible to correctly categorize unknown serum samples into one of the three groups.

A Surface Plasmon Resonance (SPR) aptasensor was developed for the detection of Brucella melitensis (B. melitensis) in milk samples. Brucellosis is a bacterial zoonotic disease with global distribution caused mostly by contaminated milk or their products. Aptamers recognizing B. melitensis were selected following a whole bacteria-SELEX procedure. Two aptamers were chosen for high affinity and high specificity. The high affinity aptamer (B70 aptamer) was immobilized on the surface of magnetic silica core-shell nanoparticles for initial purification of the target bacteria cells from milk matrix. Another aptamer, highly specific for B. melitensis cells (B46 aptamer), was used to prepare SPR sensor chips for sensitive determination of Brucella in eluted samples from magnetic purification since direct injection of milk samples to SPR sensor chips is known for a high background unspecific signal. Thus, we integrated a quick and efficient magnetic isolation step for subsequent instant detection of B. melitensis contamination in one ml of milk sample by SPR with a LOD value as low as 27 ± 11 cells.

A multivariate model was developed to attribute samples to a synthetic method used in the production of sulfur mustard (HD). Eleven synthetic methods were used to produce 66 samples for model construction. Three chemists working in both participating laboratories took part in the production, with the aim to introduce variability while reducing the influence of laboratory or chemist specific impurities in multivariate analysis. A gas chromatographic/mass spectrometric data set of peak areas for 103 compounds was subjected to orthogonal partial least squares - discriminant analysis to extract chemical attribution signature profiles and to construct multivariate models for classification of samples. For one- and two-step routes, model quality allowed the classification of an external test set (16/16 samples) according to synthesis conditions in the reaction yielding sulfur mustard. Classification of samples according to first-step methodology was considerably more difficult, given the high purity and uniform quality of the intermediate thiodiglycol produced in the study. Model performance in classification of aged samples was also investigated.

Chemical attribution signatures (CAS) associated with different synthetic routes used for the production of Russian VX (VR) were identified. The goal of the study was to retrospectively determine the production method employed for an unknown VR sample. Six different production methods were evaluated, carefully chosen to include established synthetic routes used in the past for large scale production of the agent, routes involving general phosphorus-sulfur chemistry pathways leading to the agent, and routes whose main characteristic is their innate simplicity in execution. Two laboratories worked in parallel and synthesized a total of 37 batches of VR via the six synthetic routes following predefined synthesis protocols. The chemical composition of impurities and byproducts in each route was analyzed by GC/MS-EI and 49 potential CAS were recognized as important markers in distinguishing these routes using Principal Component Analysis (PCA). The 49 potential CAS included expected species based on knowledge of reaction conditions and pathways but also several novel compounds that were fully identified and characterized by a combined analysis that included MS-CI, MS-EI and HR-MS. The CAS profiles of the calibration set were then analyzed using partial least squares discriminant analysis (PLS-DA) and a cross validated model was constructed. The model allowed the correct classification of an external test set without any misclassifications, demonstrating the utility of this methodology for attributing VR samples to a particular production method. This work is part one of a three-part series in this Forensic VSI issue of a Sweden-United States collaborative effort towards the understanding of the CAS of VR in diverse batches and matrices. This part focuses on the CAS in synthesized batches of crude VR and in the following two parts of the series the influence of food matrices on the CAS profiles are investigated.

Analysis of water and sand samples was done by reflectance measurements using a mobile phone. The phone’s screen served as light source and front view camera as detector. Reflected intensities for white, red, green and blue colors were used to do principal component analysis for classification of several compounds and their concentrations in the water. Classification of iron (III), chromium (VI) and sodium salt of humic acid was obtained using reflected intensities from blue and green light for concentrations 2-10 mg/l. Analysis of As(III) from 25-400 μg/l based on reflection of red light was performed utilizing the bleaching reaction of tincture of iodine containing starch. Enhanced sensitivity to low concentrations of arsenic was obtained by adding reflected intensities from white light to the analysis. Model colored sand samples representing discoloration caused by the presence of arsenic in groundwater were also analyzed.

A method using automated on-line solid phase extraction coupled with a high-performance liquid chromatography-tandem mass spectrometry system was developed for the determination of emerging benzotriazole UV stabilizers (BZTs) in different environmental water matrices including river water, sewage influent and effluent. Water sample was injected directly and the analytes were preconcentrated on a Polar Advantage II on-line SPE cartridge. After cleanup step the target BZTs were eluted in back flush mode and then separated on a liquid chromatography column. Experimental parameters such as sample loading flow rate, SPE cartridge, pH value and methanol ratio in the sample were optimized in detail. The method detection limits ranged from 0.21 to 2.17 ng/L. Recoveries of the target BZTs at 50 ng/L spiking level ranged from 76% to 114% and the inter-day RSDs ranged from 1% to 15%. The optimized method was successfully applied to analyze twelve water samples collected from different wastewater treatment plants and rivers, and five BZTs (UV-P, UV-329, UV-350, UV-234 and UV-328) were detected with concentrations up to 37.1 ng/L. The proposed method is simple, sensitive and suitable for simultaneous analysis and monitoring of BZTs in water samples.

A new method using ultrasonic extraction and solid phase extraction (SPE) clean-up pretreatments was developed for the analysis of mono-, di- and tri-substituted polyfluoroalkyl phosphates (abbreviated as mono-PAPs, di-PAPs and tri-PAPs) and perfluorinated phosphonic acids (PFPAs) in sludge from wastewater treatment plants (WWTPs). For the ultrasonic extraction of three mono-PAPs, three di-PAPs and three PFPAs in sludge samples, a mixture of tetrahydrofuran/acetic acid (1:1, v/v) was found to be the most suitable extraction solvent. The subsequently optimized clean-up and enrichment procedures were carried out with weak anion exchange (WAX) cartridges in-line coupled with graphitized carbon black (ENVI-Carb) tubes. Two tri-PAPs were ultrasonically extracted by acetonitrile/tetrahydrofuran (1:1, v/v) and cleaned by mixed-mode anion exchange (MAX) in-line coupled with ENVI-Carb cartridges. The analytes were analyzed by optimized high performance liquid chromatography tandem mass spectrometry (HPLC-MS/MS) method either in negative or positive ionization mode. The method quantification limits (MQLs) of the 11 analytes in sludge ranged from 0.6 to 5.1 ng/g, meanwhile the total recoveries of the pretreatment varied from 24% (6:2 mono-PAP) to 107% (PFDPA). The method was successfully applied to analyze 16 sewage sludge samples collected from seven provinces in China, and two mono-PAPs were identified with concentrations ranging from <MQLs to 10.7 ng/g.

We present a highly sensitive and selective electrode of laser-induced graphene modified with poly(phenol red) (P(PhR)@LIG) for measuring zinc nutrition in rice grains using square wave anodic stripping voltammetry (SWASV). The physicochemical properties of P(PhR)@LIG were investigated with scanning electron microscopy (SEM), energy -dispersive X-ray (EDX), Fourier infrared spectroscopy (FT-IR) and Raman spectroscopy. The modified electrode demonstrated an amplified anodic stripping response of Zn2+ due to the electropolymerization of P(PhR), which enhanced analyte adsorption during the accumulation step of SWASV. Under optimized parameters, the developed sensor provided a linear range from 30 to 3000 mu g L-1 with a detection limit of 14.5 mu g L-1. The proposed electrode demonstrated good reproducibility and good anti-interference properties. The sensor detected zinc nutrition in rice grain samples with good accuracy and the results were consistent with the standard ICP-OES method.

Chemical attribution signatures (CAS) can be used to obtain useful forensic information and evidence from illicit drug seizures. A CAS is typically generated using hyphenated chemical analysis techniques and consists of a fingerprint of the by-products and additives present in a sample. Among other things, it can provide information on the samples origin, its method of production, and the sources of its precursors. This work investigates the possibility of using multivariate CAS analysis to identify the synthetic methods used to prepare seized fentanyl analogues, independently of the analogues acyl derivatization. Three chemists working in two labs synthesized three different fentanyl analogues, preparing each one in duplicate by six different routes. The final collection of analogues (96 samples) and two intermediates (16 + 32 samples) were analysed by GC-MS and UHPLC-HRMS, and the resulting analytical data were used for multivariate modelling. Independently of analogue structure, the tested fentanyls could be classified based on the method used in the first step of their synthesis. The multivariate models ability to classify unknown samples was then evaluated by applying it to six new fentanyl analogues. Additionally, seized fentanyl samples was analysed and classified by the model.

A voltammetric electronic tongue (ET) and a conductivity meter were used to predict amounts of detergents in process water from washing machines. The amount of detergent in over sixty samples was also determined by a HPLC reference method. Prediction was more accurate for the electronic tongue, but both techniques could be used. The composition of the detergent, e.g. supporting electrolyte, is an important factor for the ability to predict the detergent quantity by conductivity. Also two different surfactants, alkyl benzyl sulfonate (ABS) and etoxylated fatty alcohol (EOA), were fingerprinted by the HPLC. Their behaviour during the wash cycle differs from each other, ABS rinses away in the same proportions as the supporting electrolyte, but EOA appears to stay within the machine and laundry. Prediction models for ABS are accurate both with ET and conductivity meter, mostly due to the correlation with supporting electrolyte. The behaviour of EOA, with almost no correlation to the supporting electrolyte makes it difficult to predict using conductivity but ET prediction models give promising indications of its capabilities. © 2008 Elsevier B.V. All rights reserved.

The analytical method of Gd determination was developed with the aim to analyse Gd-148 in environmental and bioassay samples. It involves the use of anion exchange resin, extraction chromatography, and cation exchange resin. Alkaline fusion and calcium oxalate co-precipitation are used for solid samples dissolution and liquid samples preconcentration, respectively. Total method recovery was tested with natural Gd (Gd-157) using ICP-QQQ-MS. A maximum total recovery of 75 % was obtained.

A sandwich-type nanostructured immunosensor based on carboxylated multi-walled carbon nanotube (CMWCNT)-embedded whiskered nanofibres (WNFs) was developed for detection of cardiac Troponin I (cTnI). WNFs were directly fabricated on glassy carbon electrodes (GCE) by removing the sacrificial component (polyethylene glycol, PEG) after electrospinning of polystyrene/CMWCNT/PEG nanocomposite nanofibres, and utilised as a transducer layer for enzyme-labeled amperometric immunoassay of cTnI. The whiskered segments of CMWCNTs were activated and utilised to immobilise anti-cTnT antibodies. It was observed that the anchored CMWCNTs within the nanofibres were suitably stabilised with excellent electrochemical repeatability. A sandwich-type immuno-complex was formed between cTnI and horseradish peroxidase-conjugated anti-cTnI (HRP-anti-cTnI). The amperometric responses of the immunosensor were studied using cyclic voltammetry (CV) through an enzymatic reaction between hydrogen peroxide and HRP conjugated to the secondary antibody. The nanostructured immunosensor delivered a wide detection range for cTnI from the clinical borderline for a normal person (0.5-2 ng mL(-1)) to the concentration present in myocardial infarction patients (amp;gt; 20 ng mL(-1)), with a detection limit of similar to 0.04 ng mL(-1). It also showed good reproducibility and repeatability for three different cTnI concentration (1, 10 and 25 ng mL(-1)) with satisfactory relative standard deviations (RSD). Hence, the proposed nanostructured immunosensor shows potential for point-of-care testing.

The effect of sequential extraction of trace metals on sulphur (S) speciation in anoxic sludge samples from two lab-scale biogas reactors augmented with Fe was investigated. Analyses of sulphur K-edge X-ray absorption near edge structure (S XANES) spectroscopy and acid volatile sulphide (AVS) were conducted on the residues from each step of the sequential extraction. The S speciation in sludge samples after AVS analysis was also determined by S XANES. Sulphur was mainly present as FeS (~60% of total S) and reduced organic S (~30% of total S), such as organic sulphide and thiol groups, in the anoxic solid phase. Sulphur XANES and AVS analyses showed that during first step of the extraction procedure (the. removal of exchangeable cations), a part of the FeS fraction corresponding to 20% of total S was transformed to zero-valent S, whereas Fe was not released into the solution during this transformation. After the last extraction step (organic/sulphide fraction) a secondary Fe phase was formed. The change in chemical speciation of S and Fe occurring during sequential extraction procedure suggests indirect effects on trace metals associated to the FeS fraction that may lead to incorrect results. Furthermore, by S XANES it was verified that the AVS analysis effectively removed the FeS fraction. The present results identified critical limitations for the application of sequential extraction for trace metal speciation analysis outside the framework for which the methods were developed.

We developed a fully integrated smart sensing device for on-site testing of food to detect trace formaldehyde (FA). A nano-palladium grafted laser-induced graphene (nanoPd@LIG) composite was synthesized by one-step laser irradiation of a symbolscript precursor. The composite was synthesized in the form of a three-electrode sensor on a polymer substrate. The electrochemical properties and morphology of the fabricated composite were characterized and the electrochemical kinetics of FA oxidation at the nanoPd@LIG electrode were investigated. The nanoPd@LIG electrode was combined with a smart electrochemical sensing (SES) device to determine FA electrochemically. The proposed SES device uses near field communication (NFC) to receive power and transfer data between a smartphone interface and a battery-free sensor. The proposed FA sensor exhibited a linear detection range from 0.01 to 4.0 mM, a limit of detection of 6.4 mu M, good reproducibility (RSDs between 2.0 and 10.1%) and good anti-interference properties for FA detection. The proposed system was used to detect FA in real food samples and the results correlated well with the results from a commercial potentiostat and a spectrophotometric analysis.

In this study, an electrochemical biosensor was developed for highly sensitive and specific detection of target miRNA-155. The structure was formed by the hybridization of a tetrahedral DNA nanostructure-based biomolecular probe assembled on 3D nitrogen-doped reduced graphene oxide/gold nanoparticles (3D N-doped rGO/AuNPs) electrode surface. Upon addition of target miRNA-155, the gold and silver nanorod/thionine/complementary DNA (AuAgNR/Thi/F) was hybridized with the target, and used for signal amplification, catalyzing the reduction of Thi as an electron mediator. Due to the signal amplification by the enhanced immobilization of DNA on the surface of 3D N-doped rGO/AuNPs electrode and AuAgNR/Thi, coupling the low background signal produced by blank solution, electrochemical performance of the device was optimized to be proportional to miRNA-155 concentration in the range of 1 x 10(-11) to 1 x 10(-4) M with a detection limit of 1 x 10(-12) M. In addition, direct detection in serum is demonstrated with high specificity. Thus, this biosensor is potentially applicable for microRNA detection in medical research and early clinical diagnosis.

Acute intoxication incidents due to neurotoxic organophosphate (OP) insecticides are occasionally reported, related either to suicidal attempts or occupational exposure due to the misuse of protective equipment. Among them, chlorpyrifos is a compound related to great controversy, which is still authorized and easily accessible in many countries around the world. However, to screen for its exposure markers, instrumental methods are commonly applied, which cannot enable rapid monitoring at an early stage of an intoxication. Therefore, in this study, a microfluidic paper-based analytical device (mu PAD) able to rapidly screen for chlorpyrifos-oxon, the toxic chlorpyrifos metabolite, in human serum was developed and fully validated. The mu PAD combines wax-printed butyrylcholinesterase (BChE) paper sensors, a lab-on-a-chip (LOC) prototype injector and a smartphone as the analytical detector. In principle, the wax-printed strips with adsorbed BChE are embedded into LOC injectors able to deliver samples and reagents on-demand. A smartphone reader was used to monitor the color development on the strips providing binary qualitative results. mu PAD method performance characteristics were thoroughly evaluated in terms of specificity, detection capability (CC beta) and ruggedness. The developed analytical platform is rapid (results within 10 min), cost-efficient (0.70 (sic)), potentially applicable at the point-of-need and attained a low CC beta (10 mu g L-1 in human serum). Finally, mu PAD characteristics were critically compared to wellestablished methods, namely an in-house BChE microplate assay and liquid chromatography tandem mass spectrometry.

In this paper, we explore the combination of electrochemical impedance spectroscopy (EIS) and multivariate data analysis to evaluate the concentration and pH of an industrial cutting fluid. These parameters are vital for the performance of for instance tooling processes, and an on-line monitoring system would be very beneficial. It is shown that both the total impedance and the phase angle contain information that allows the simultaneous discrimination of the concentration and the pH. The final evaluation was made with a regression model, namely partial least squares (PLS). This approach provided a way to quickly and simply find the correlation between EIS data and the sought parameters. The results from the measurements showed the possibility to predict the concentration and pH level, indicating the potential of this method for on-line measurements.

Food allergies are hypersensitivity immune responses triggered by (traces of) allergenic compounds in foods and drinks. The recent trend towards plant-based and lactose-free diets has driven an increased consumption of plant -based milks (PBMs) with the risk of cross-contamination of various allergenic plant-based proteins during the food manufacturing process. Conventional allergen screening is usually performed in the laboratory, but portable biosensors for on-site screening of food allergens at the production site could improve quality control and food safety. Here, we developed a portable smartphone imaging surface plasmon resonance (iSPR) biosensor composed of a 3D-printed microfluidic SPR chip for the detection of total hazelnut protein (THP) in commercial PBMs and compared its instrumentation and analytical performance with a conventional benchtop SPR. The smartphone iSPR shows similar characteristic sensorgrams compared with the benchtop SPR and enables the detection of trace levels of THP in spiked PBMs with the lowest tested concentration of 0.625 mu g/mL THP. The smartphone iSPR achieved LoDs of 0.53, 0.16, 0.14, 0.06, and 0.04 mu g/mL THP in 10x-diluted soy, oat, rice, coconut, and almond PBMs, respectively, with good correlation with the conventional benchtop SPR system (R2 0.950-0.991). The portability and miniaturized characteristics of the smartphone iSPR biosensor platform make it promising for the future on-site detection of food allergens by food producers.

It is hard to quantify the trace pollutants in the environment without the corresponding reference standards. Structure identifications of unknown organic pollutants are thus of great importance in environmental analysis. As for polybrominated diphenyl ethers (PBDE) with one substituent of methoxyl group, there are 837 congeners, but only 32 standards are commercially available. In this work, an effective method based on gas chromatography coupled with mass spectrometry (GC-MS) was proposed to predict the potential structures of methoxylated polybrominated diphenyl ethers (MeO-PBDEs). The mass fragmentation pattern using SIM mode not only provided the useful information on the substitution position of methoxyl group, the number of Br atoms, but also guaranteed the high sensitivity for trace analysis. Br distribution patterns of the unknown MeO-PBDEs were revealed by a linear regression model with dummy variables which described the retention time relationship between MeO-PBDEs and the corresponding PBDEs on different types of GC columns. This method was successfully used to identify three new MeO-PBDEs metabolites of BDE-28 as 4-MeO-BDE-22, 4'-MeO-BDE-25 and 4-MeO-BDE-31 in the pumpkins. Therefore, the newly developed structure prediction model based on GC-MS behavior is helpful in the evaluation of unknown PBDE metabolites in the environment.

An extraction procedure for extracting organic mercury species including methylmercury (MeHg) and ethylmercury (EtHg) from petroleum samples was developed. Three extraction methods (shaking, ultrasonic and microwave assisted extraction) using different extraction solvents (TMAH, KOH/CH3OH, HCl and acidic CuSO4/KBr) were investigated by comparing the extraction efficiency of the organic mercury species. Microwave assisted extraction at 60 W for 5 min using TMAH (tetramethylammonium hydroxide, 25%, m/v) provided the most satisfactory extraction efficiency for MeHg and EtHg in petroleum at 86.7% ± 3.4% and 70.6% ± 5.9%, respectively. Speciation analysis of mercury was done by on-line coupling of high performance liquid chromatography with cold vapor generation atomic fluorescence spectrometry (HPLC-CV-AFS). The proposed method was successfully applied to analyze several crude oil and light oil samples. The concentrations of MeHg ranged from under detection limit to 0.515 ng g(-1), whereas EtHg was not detected in the samples. This method can be a very useful tool in evaluating the risk of mercury emissions from petroleum.