RESUMO
Cocaine use has been reported for more than 2500 years, but along this period of time its damage to society in general became evident. Nowadays, cocaine is classified as an illicit drug and studies which give support to drug enforcement institutions, particularly in the area of police intelligence, are very relevant. Often, trafficked cocaine is not traded in its pure form, but mixed with adulterants and diluents. In the analysis of seized samples, the reference method is based on gas chromatography, however the interest in the use of vibrational spectroscopy has increased. This work aims at developing a method for determination of the concentrations of cocaine, adulterants and diluents in cocaine samples employing Attenuated Total Reflectance Fourier Transform Infrared Spectroscopy (ATR-FTIR) associated with Multivariate Curve Resolution with Alternating Least-Squares (MCR-ALS). A total of 6 adulterants, 3 diluents, 2 forms of cocaine (base and hydrochloride) were determined and the method developed based on 55 synthetic mixtures prepared according to a mixture design and 20 seized samples. For validation purposes 708 seized samples and 9 synthetic mixtures were analyzed. The results proved to be satisfactory, showing that the proposed method has a great potential in the classification of the chemical form of cocaine, identification of adulterants, diluents and cocaine in seized samples, as well as providing an estimate for their concentration.
Assuntos
Cocaína/química , Contaminação de Medicamentos , Drogas Ilícitas/química , Toxicologia Forense/métodos , Humanos , Análise dos Mínimos Quadrados , Espectrofotometria InfravermelhoRESUMO
A new multivariate regression model, named Error Covariance Penalized Regression (ECPR) is presented. Following a penalized regression strategy, the proposed model incorporates information about the measurement error structure of the system, using the error covariance matrix (ECM) as a penalization term. Results are reported from both simulations and experimental data based on replicate mid and near infrared (MIR and NIR) spectral measurements. The results for ECPR are better under non-iid conditions when compared with traditional first-order multivariate methods such as ridge regression (RR), principal component regression (PCR) and partial least-squares regression (PLS).
RESUMO
Middle infrared spectroscopy and multivariate analysis have been applied for the development of methods to perform both quantitative and qualitative analysis of real drug samples seized by the Brazilian Police Federal (BPF). Currently, quantification of cocaine and determination of adulterants in seizures is performed using gas chromatography with flame ionization detection. However, this technique requires a relatively complex sample preparation, higher time of analysis, the destruction of sample and a high cost. In this context, this paper presents a simpler method to quantify cocaine and its major adulterants in seized materials. Out of 375 seizures, taken within a time frame of 2009-2013. A total of 1085 samples were analyzed of which 500 were selected for the calibration set and 585 for the validation set. Cocaine concentration in seized samples was determined by using middle infrared spectroscopy and partial least squares regression (PLSR), obtaining an average prediction error of 3.0% (w/w), precision of 2.0 and 11.8% (w/w) of minimum detectable cocaine concentration in a range varying from 24.2 to 99.9% (w/w). Results indicate that the developed method is able to discriminate between cocaine hydrochloride and free base samples, to quantify cocaine content as well as to estimate the concentration of main adulterants phenacetin, benzocaine, caffeine, lidocaine and aminopyrine.
Assuntos
Cocaína/análise , Contaminação de Medicamentos , Drogas Ilícitas/química , Análise dos Mínimos Quadrados , Espectrofotometria Infravermelho , Brasil , Tráfico de Drogas , HumanosRESUMO
Cocaine sample correlation provides important information in the identification of traffic networks. However, available methods for estimating if samples are linked or not require the use of previous police investigation and forensic expert knowledge regarding the number of classes and provide thresholds that are both static and data set specific. In this paper, a novel unsupervised linkage threshold method (ULT) based on chemometric analysis is described and applied to the analysis of headspace gas chromatography mass spectrometry (HS-GC/MS) data of more than 250 real cocaine hydrochloride samples seized by Brazilian Federal Police. The method is capable of establishing linkage thresholds that do not require any prior information about the number of classes or distribution of the samples and can be dynamically updated as the data set changes. It is envisaged that the ULT method may also be applied to other forensic expertise areas where limited population knowledge is available and data sets are continually modified with the inflow of new information.
Assuntos
Cocaína/química , Resíduos de Drogas/análise , Cromatografia Gasosa-Espectrometria de Massas , Solventes/química , Brasil , Ciências ForensesRESUMO
Recent information from various sources suggests that a new illicit drug, called "oxi", is being spread across Brazil. It would be used in the smoked form and it would look like to crack cocaine: usually small yellowish or light brown stones. As fully released in the media, "oxi" would differ from crack cocaine in the sense that crack would contain carbonate or bicarbonate salts whereas "oxi" would include the addition of calcium oxide and kerosene (or gasoline). In this context, this work presents a chemical profiling comparative study between "oxi" street samples seized by the Civil Police of the State of Acre (CP/AC) and samples associated with both international and interstate drug trafficking seized by the Brazilian Federal Police in Acre (FP/AC). The outcome of this work assisted Brazilian authorities to stop inaccurate and alarmist releases on this issue. It may be of good use by the forensic community in order to better understand matters in their efforts to guide local law enforcement agencies in case such claims reach the international illicit market.
RESUMO
This paper proposes a new method for determination of amoxicillin in pharmaceutical suspension formulations, based on transflectance near infrared (NIR) measurements and partial least squares (PLS) multivariate calibration. A complete methodology was implemented for developing the proposed method, including an experimental design, data preprocessing by using multiple scatter correction (MSC) and outlier detection based on high values of leverage, and X and Y residuals. The best PLS model was obtained with seven latent variables in the range from 40.0 to 65.0 mg mL(-1) of amoxicillin, providing a root mean square error of prediction (RMSEP) of 1.6 mg mL(-1). The method was validated in accordance with Brazilian and international guidelines, through the estimate of figures of merit, such as linearity, precision, accuracy, robustness, selectivity, analytical sensitivity, limits of detection and quantitation, and bias. The results for determinations in four commercial pharmaceutical formulations were in agreement with the official high performance liquid chromatographic (HPLC) method at the 99% confidence level. A pseudo-univariate calibration curve was also obtained based on the net analyte signal (NAS). The proposed chemometric method presented the advantages of rapidity, simplicity, low cost, and no use of solvents, compared to the principal alternative methods based on HPLC.
Assuntos
Amoxicilina/análise , Calibragem , Cromatografia Líquida de Alta Pressão , Análise dos Mínimos Quadrados , Limite de Detecção , Padrões de Referência , Reprodutibilidade dos Testes , Espectroscopia de Luz Próxima ao Infravermelho , SuspensõesRESUMO
In non-ideal scenarios involving partial or non-breastfeeding, cow's milk-based dairy products are mainstream in infant feeding. Therefore, it is important to study the concentrations of potentially neurotoxic contaminants (Pb and Cd) and their respective counteracting elements (Ca and Zn) in infant dairy products. Fifty-five brands of infant formulas and milk sold in Brasilia, Brazil were analyzed. The dairy products came from areas in the central-west (26%), southeast (29%) and south of Brazil (36%) extending as far as Argentina (7%) and the Netherlands (2%). For toxic Pb and Cd, median concentrations in powdered samples were 0.109 mg/kg and 0.033 mg/kg, respectively; in fluid samples median Pb concentration was 0.084 mg/kg, but median Cd concentration was below the limit of detection and overall values were below reference safety levels. However, 62% of these samples presented higher Pb concentration values than those established by FAO/WHO. Although the inverse correlation between Cd and Zn (Spearman r = -0.116; P = 0.590) was not statistically significant, the positive correlation between Ca and Pb was (Spearman r = 0.619; P < 0.0001). Additionally, there was a significant correlation between Pb and Cd. Furthermore, the study also revealed that provision of the essential trace element Zn in infant formulas can provide adequate amounts of the recommended daily requirements. Infant formulas and milk sold for consumption by infants and children can be an efficient tool to monitor neurotoxic metal risk exposure among young children.
Assuntos
Cádmio/análise , Alimentos Infantis/análise , Chumbo/análise , Leite/química , Animais , Brasil , Eletroquímica , Humanos , Limite de Detecção , Espectrofotometria AtômicaRESUMO
A variable selection methodology based on genetic algorithm (GA) was applied in a bilinear least squares model (BLLS) with second-order advantage, in three distinct situations, for determination by HPLC-DAD of the pesticides carbaryl (CBL), methyl thiophanate (TIO), simazin (SIM) and dimethoate (DMT) and the metabolite phthalimide (PTA) in wine. The chromatographic separation was carried out using an isocratic elution with 50:50 (v/v) acetonitrile:water as mobile phase. Preprocessing methods were performed for correcting the chromatographic time shifts, baseline variation and background. The optimization by GA provided a significant reduction of the errors, where for SIM and PTA a decrease of three times the value obtained using all variables, and an improvement in the distribution of them, reducing the observed bias in the results were observed. Comparing the RMSEP of the optimized model with the uncertainty estimates of the reference values it is observed that GA can be a very useful tool in second-order models.