RESUMO
BACKGROUND: the chemometric processing of second-order chromatographic-spectral data is usually carried out with the aid of multivariate curve resolution-alternating least-squares (MCR-ALS). Recently, an alternative procedure was described based on the estimation of image moments for each data matrix and subsequent application of multiple linear regression after suitable variable selection. RESULTS: The analysis of both simulated and experimental data leads to the conclusion that the image moment method, although can cope with chromatographic lack of reproducibility across injections, it only performs well in the absence of uncalibrated interferents. MCR-ALS, on the other hand, provides good analytical results in all studied situations, whether the test samples contain uncalibrated interferents or not. SIGNIFICANCE: The results are useful to assess the real usefulness of newly proposed methodologies for second-order calibration in the case of chromatographic-spectral data sets, especially when samples contain unexpected chemical constituents.
RESUMO
BACKGROUND: the chemometric processing of second-order chromatographic-spectral data is usually carried out with the aid of multivariate curve resolution-alternating least-squares (MCR-ALS). When baseline contributions occur in the data, the background profile retrieved with MCR-ALS may show abnormal lumps or negative dips at the position of the remaining component peaks. RESULTS: The phenomenon is shown to be due to remaining rotational ambiguity in the obtained profiles, as confirmed by the estimation of the boundaries of the range of feasible bilinear profiles. To avoid the abnormal features in the retrieved profile, a new background interpolation constraint is proposed and described in detail. Both simulated and experimental data are employed to support the need of the new MCR-ALS constraint. In the latter case, the estimated analyte concentrations agreed with those previously reported. SIGNIFICANCE: The developed procedure helps to reduce the extent of rotational ambiguity in the solution and to better interpret the results on physicochemical grounds.
RESUMO
Cocoa butter (CB) is an ingredient traditionally used in the manufacturing of chocolates, but its availability is decreasing due to its scarcity and high cost. For this reason, other vegetable oils, known as cocoa butter equivalents (CBE), are used to replace CB partially or wholly. In the present work, two Peruvian vegetable oils, coconut oil (CNO) and sacha inchi oil (SIO), are proposed as novel CBEs. Confocal Raman microscopy (CRM) was used for the chemical differentiation and polymorphism of these oils with CB based on their Raman spectra. To analyze their miscibility, two types of blends were prepared: CB with CNO, and CB with SIO. Both were prepared at 5 different concentrations (5%, 15%, 25%, 35%, and 45%). Raman mapping was used to obtain the chemical maps of the blends and analyze their miscibility through distribution maps, histograms and relative standard deviation (RSD). These values were obtained with multivariate curve resolution-alternating least squares. The results show that both vegetable oils are miscible with CB at high concentrations: 45% for CNO and 35% for SIO. At low concentrations, their miscibility decreases. This shows that it is possible to consider these vegetable oils as novel CBEs in the manufacturing of chocolates.
RESUMO
Adenosine is a purine nucleoside that is present in all human cells and is essential for regulating certain physiological activities in tissues and organs. Since adenosine is considered to be a potential cancer biomarker in urine, its determination may be crucial for the early diagnosis and non-invasive monitoring of cancer. Herein, we present a label-free method to quantify urinary adenosine using surface-enhanced Raman spectroscopy (SERS) and multivariate curve resolution-alternating least squares (MCR-ALS). Ring-oven preconcentration and direct deposition of monodisperse gold nanoparticles on filter paper were employed to improve the sampling efficiency. Further, MCR-ALS (assessed with and without a correlation constraint), the standard addition method and pH controls were combined to compensate for the matrix effect and to address overlapping bands in the analysis of human urine samples. As a result, the proposed method showed to be sensitive (LOD varying between 3.8 and 4.9⯵molâ¯L-1, S/Râ¯=â¯3), reproducible (RSD less than ±â¯15%), and selective over other nucleosides (guanosine, cytidine, thymidine and uridine) and unknown interferences (second-order advantage). This is the first report of a SERS-chemometric method applied to urinary adenosine sensing at physiologically relevant concentrations, with minimal sample preparation, and has strong potential to be a valuable tool in cancer research.
RESUMO
Octyl p-methoxycinnamate (OMC) is one of the most widely used sunscreen agents. However, the efficiency of OMC as UV filter over time is affected due to the formation of the cis-isomer which presents a markedly lower extinction coefficient (εcis=12,600L mol-1cm-1 at 291nm) than the original trans-isomer (εtrans=24,000L mol-1cm-1 at 310nm). In this work, a novel carrier for OMC based on an oil-in-water microemulsion is proposed in order to improve the photostability of this sunscreen. The formulation was composed of 29.2% (w/w) of a 3:1 mixture of ethanol (co-surfactant) and decaethylene glycol mono-dodecyl ether (surfactant), 1.5% (w/w) of oleic acid (oil phase) and 69.2% (w/w) of water. This microemulsion was prepared in a simple way, under moderate stirring at 25°C and using acceptable, biocompatible and accessible materials for topical use. OMC was incorporated in the vehicle at a final concentration of 5.0% (w/w), taking into account the maximum permitted levels established by international norms. Then, a photolysis study of the loaded formulation was performed using a continuous flow system. The direct photolysis was monitored over time by molecular fluorescence. The recorded spectra data between 370 y 490nm were analyzed by multivariate curve resolution-alternating least squares algorithm. The kinetic rate constants corresponding to the photolysis of the trans-OMC were calculated from the concentration profiles, resulting in 0.0049s-1 for the trans-OMC loaded microemulsion and 0.0131s-1 for the trans-OMC in aqueous media. These results demonstrate a higher photostability of the trans-OMC when loaded in the proposed vehicle with respect to the free trans-OMC in aqueous media.
RESUMO
Second-order liquid chromatographic data with multivariate spectral (UV-vis or fluorescence) detection usually show changes in elution time profiles from sample to sample, causing a loss of trilinearity in the data. In order to analyze them with an appropriate model, the latter should permit a given component to have different time profiles in different samples. Two popular models in this regard are multivariate curve resolution-alternating least-squares (MCR-ALS) and parallel factor analysis 2 (PARAFAC2). The conditions to be fulfilled for successful application of the latter model are discussed on the basis of simple chromatographic concepts. An exhaustive analysis of the multivariate calibration models is carried out, employing both simulated and experimental chromatographic data sets. The latter involve the quantitation of benzimidazolic and carbamate pesticides in fruit and juice samples using liquid chromatography with diode array detection, and of polycyclic aromatic hydrocarbons in water samples, in both cases in the presence of potential interferents using liquid chromatography with fluorescence spectral detection, thereby achieving the second-order advantage. The overall results seem to favor MCR-ALS over PARAFAC2, especially in the presence of potential interferents.