Abstract: This research is aimed to the study and application of an electrochemical immunosensor for the detection of ovalbumin (OVA) from egg white (or albumen) used as a binder in some works of art, such as some historical photographic prints and tempera paintings. The immunosensor takes advantage of the interesting biodetection capabilities offered by nanoelectrode ensembles (NEEs). The NEEs used to this aim are prepared by template deposition of gold nanoelectrodes within the pores of track-etched polycarbonate (PC) membranes. The affinity of polycarbonate for proteins is exploited to capture OVA from the aqueous extract obtained by incubation in phosphate buffer of a small sample fragment (<1 mg). The captured protein is reacted selectively with anti-OVA antibody, labelled with glucose oxidase (GOx). In the case of positive response, the addition of the GOx substrate (i.e. glucose) and a suitable redox mediator (a ferrocenyl derivative) reflects in the up rise of an electrocatalytic oxidation current, which depends on the OVA amount captured on the NEE, this amount correlating with OVA concentration in the extract. After optimization, the sensor is successfully applied to identify OVA in photographic prints dating back to the late 19th century, as well as in ancient tempera paintings from the 15th and 18th centuries.

Abstract: Electrochemical strategies to selectively detect heroin in street samples without the use of complicated electrode modifications were developed for the first time. For this purpose, heroin, mixing agents (adulterants, cutting agent, and impurities), and their binary mixtures were subjected to square wave voltammetry measurements at bare graphite electrodes at pH 7.0 and pH 12.0, in order to elucidate the unique electrochemical fingerprint of heroin and mixing agents as well as possible interferences or reciprocal influences. Adjusting the pH from pH 7.0 to pH 12.0 allowed a more accurate detection of heroin in the presence of most common mixing agents. Furthermore, the benefit of introducing a preconditioning step prior to running square wave voltammetry on the electrochemical fingerprint enrichment was explored. Mixtures of heroin with other drugs (cocaine, 3,4-methylenedioxymethamphetamine, and morphine) were also tested to explore the possibility of their discrimination and simultaneous detection. The feasibility of the proposed electrochemical strategies was tested on realistic heroin street samples from forensic cases, showing promising results for fast, on-site detection tools of drugs of abuse.

Abstract: A selective electrochemical sensor for direct detection of cocaine was developed based on molecularly imprinted polymers electropolymerized onto graphene-modified electrodes. Palladium nanoparticles were integrated in the sensing layer for the benefit of enhancing the communication between imprinted sites and electrode and improving their homogenous distribution. The molecularly imprinted polymer was synthesized by cyclic voltammetry using p-aminobenzoic acid as high affinity monomer selected by computational modeling, and cocaine as template molecule. Experimental parameters related to the electrochemical deposition of palladium nanoparticles, pH, composition of electropolymerization mixture, extraction and rebinding condition were studied and optimized. Under optimized conditions the oxidation peak current varied linearly with cocaine concentration in the range of 100-500 µM, with a detection limit of 50 µM (RSD 0.71%, n=3). The molecularly imprinted sensor was able to detect cocaine in saliva and river water with good recoveries after sample pretreatment and was successfully applied for screening real street samples for cocaine.

Abstract: The illicit consumption of heroin is an increasing concern in our society. For this reason, rapid analytical methods to seize heroin samples in the field are of paramount importance to hinder drug trafficking, and thus prevent the availability of heroin in the drug market. The present work reports on the enriched electrochemical fingerprint of heroin, allowing its selective detection in street samples, based on the use of electrochemical pretreated screen printed electrodes (p-SPE). The voltammetric identification is built on two oxidation peaks of both heroin and its degradation product 6-monoacetylmorphine (6-MAM), generated in alkaline conditions. Interestingly, an anodic pretreatment of the screen printed electrodes (SPE) shifts the peak potential of paracetamol (the most encountered cutting agent in heroin seizures), allowing the detection of 6-MAM peak, overlapping with the paracetamol signal in the case of untreated SPE. Subsequently, the characterization of the p-SPE with scanning electron microscopy, cyclic voltammetry, electrochemical impedance spectroscopy, Raman and Fourier transform infrared (FTIR) spectroscopy is provided to demonstrate local changes on the surface of the electrode. From an analytical perspective, p-SPE provide higher sensitivity (0.019 μA μM-1), excellent reproducibility (6-MAM, RSD = 2.85%, and heroin RSD = 0.91%, n = 5) and lower limits of detection (LOD) (5.2 μM) in comparison to untreated SPE. The proposed protocol which integrates a tailor-made script is interrogated against common cutting agents, and finally, validated with the screening of 14 street samples, also analyzed by standard methods. Besides, a comparison with portable spectroscopic techniques on the confiscated samples shows the better performance of the electrochemical strategy. Overall, this sensing approach offers promising results for the rapid on-site profiling of suspicious heroin samples, also in the presence of paracetamol.

Abstract: Iron (Fe) and other trace elements such as Zn, Mn, Ni and Cu are known as key-factors in marine biogeochemical cycles. It is believed that ocean primary productivity blooms in iron deficient regions can be triggered by iron in aeolian dust. Up to now, scarce aerosol elemental composition, based on measurements over sea at the Western South Atlantic (WSA), exist. An association between the Patagonian semi-desert dust/Fe and chlorophyll-a variability at the Argentinean continental shelf is essentially inferred from models. We present here experimental data of Fe enriched aerosols over the WSA between latitudes 22°S62°S, during 4 oceanographic campaigns between 2002 and 2005. These data allowed inferring the atmospheric Fe flux onto different latitudinal bands which varied from 30.4 to 1688 nmolFe m−2 day−1 (October 29thNovember 15th, 2003); 5.831586 nmolFe m−2 day−1 (February 15thMarch 6th, 2004) and 4.73586 nmolFe m−2 day−1(October 21stNovember 5th, 2005).

Abstract: Energy-dispersive X-ray fluorescence was used for the analysis of hair samples from three different age groups of the Sudanese population. Hair samples were digested in a mixture of nitric and perchloric acids and the metals were then precipitated with ammonium pyrrolidine dithiocarbamate. The variations of the Fe, Cu, Zn and Pb content of hair with age were investigated. The averages of the elemental concentrations in each age group were compared with the other age groups and with literature values. The correlation of each pair of elements in the hair samples was also investigated.

Abstract: Large quantities of illicit drugs are frequently seized by law enforcement. In such cases, a representative number of samples needs to be quickly examined prior to destruction. No procedure has yet been set up which rapidly provides information regarding the homogeneity of the samples, the presence of controlled substances and the degree of purity. This study establishes a protocol for fast analysis of cocaine and its most common cutting agent, levamisole, in large seizures. The protocol is based on a hypergeometric sampling approach combined with FTIR spectrometry and Support Vector Machines (SVM) algorithms as analysis methods. To demonstrate the practical use of this approach, five large cocaine seizures (consisting between 45 and 85 units) were analysed simultaneously with GC-MS, GC-FID and a portable FTIR spectrometer using Attenuated Total Reflectance (ATR) sampling combined with SVM models. According to the hypergeometric sampling plan of the Drugs Working Group ENFSI guidelines, the required number of subsamples ranged between 19 and 23. Considering the identification analyses, the SVM models detected cocaine and levamisole in all subsamples of cases 1 to 5 (100% correct classification), which was confirmed by GC-MS analysis. Considering the quantification analyses, the SVM models were able to estimate the cocaine and levamisole content in each subsample, compared to GC-FID data. The developed strategy is easy, cost effective and provides immediate information about both the presence and concentration of cocaine and levamisole. By using this new strategy, the number of confirmation analyses with laborious and expensive chromatographic techniques could be significantly reduced.

Abstract: Spectroscopic techniques combined with chemometrics are a promising tool for analysis of seized drug powders. In this study, the performance of three spectroscopic techniques [Mid-InfraRed (MIR), Raman and Near-InfraRed (NIR)] was compared. In total, 364 seized powders were analyzed and consisted of 276 cocaine powders (with concentrations ranging from 4 to 99 w%) and 88 powders without cocaine. A classification model (using Support Vector Machines [SVM] discriminant analysis) and a quantification model (using SVM regression) were constructed with each spectral dataset in order to discriminate cocaine powders from other powders and quantify cocaine in powders classified as cocaine positive. The performances of the models were compared with gas chromatography coupled with mass spectrometry (GC-MS) and gas chromatography with flame-ionization detection (GC-FID). Different evaluation criteria were used: number of false negatives (FNs), number of false positives (FPs), accuracy, root mean square error of cross-validation (RMSECV) and determination coefficients (R-2). Ten colored powders were excluded from the classification data set due to fluorescence background observed in Raman spectra. For the classification, the best accuracy (99.7%) was obtained with MIR spectra. With Raman and NIR spectra, the accuracy was 99.5% and 98.9%, respectively. For the quantification, the best results were obtained with NIR spectra. The cocaine content was determined with a RMSECV of 3.79% and a R-2 of 0.97. The performance of MIR and Raman to predict cocaine concentrations was lower than NIR, with RMSECV of 6.76% and 6.79%, respectively and both with a R-2 of 0.90. The three spectroscopic techniques can be applied for both classification and quantification of cocaine, but some differences in performance were detected. The best classification was obtained with MIR spectra. For quantification, however, the RMSECV of MIR and Raman was twice as high in comparison with NIR. Spectroscopic techniques combined with chemometrics can reduce the workload for confirmation analysis (e.g., chromatography based) and therefore save time and resources.