Net Analyte Signal Research Articles

Pretreatments by means of orthogonal projections

This article describes several linear pretreatments based on orthogonal projections. The main differences of these pretreatments lie in the way the information to be removed are identified, using calibration dataset, pure spectra, experimental designs or mathematical models. Removing all the undesired spectral information yields spectra proportional to the net analyte signal, so it is important to collect the most complete information possible, using the complementarities of different approaches. The correction should then be processed with a single Euclidian orthogonal projection that gathers all the information, rather than with successive operations. By embedding Euclidian orthogonal projections into the calibration, it is not necessary to reapply them to new datasets.

The Use of Net Analyte Signal Aspect in Univariate Calibration for Simultaneous Determination of Guaifenesin, Pseudoephedrine and Chlorpheniramine in Cough Syrup Formulations

The Use of Net Analyte Signal Aspect in Univariate Calibration for Simultaneous Determination of Guaifenesin, Pseudoephedrine and Chlorpheniramine in Cough Syrup Formulations

Net analyte signal with floating reference theory in non-invasive blood glucose sensing by near-infrared spectroscopy

Based on the floating reference theory, a new method for extracting the net analyte signal (NAS) is proposed. The noise background subspace is spanned by spectra at the floating radial reference point, and then, the spectra at the measurement point are projected on the subspace. Thereafter, the glucose concentrations in intralipid solutions are investigated through Monte Carlo simulation and experiments, and the partial least squares (PLS) models with and without NAS analysis are built. The root mean square errors of calibration and prediction reach to 28.87% and 27.33%, respectively. The results confirm the existence of information induced by glucose concentration variations as well as the validity of the floating reference theory.

Net Analyte Signal Standard Additions Method for Simultaneous Determination of Sulfamethoxazole and Trimethoprim in Pharmaceutical Formulations and Biological Fluids

The applicability of a novel net analyte signal standard addition method (NASSAM) to the resolving of overlapping spectra corresponding to the sulfamethoxazole and trimethoprim was verified by UV-visible spectrophotometry. The results confirmed that the net analyte signal standard additions method with simultaneous addition of both analytes is suitable for the simultaneous determination of sulfamethoxazole and trimethoprim in aqueous media. Moreover, applying the net analyte signal standard additions method revealed that the two drugs could be determined simultaneously with the concentration ratios of sulfamethoxazole to trimethoprim varying from 1:35 to 60:1 in the mixed samples. In addition, the limits of detections were 0.26 and 0.23 μmol L-1for sulfamethoxazole and trimethoprim, respectively. The proposed method has been effectively applied to the simultaneous determination of sulfamethoxazole and trimethoprim in some synthetic, pharmaceutical formulation and biological fluid samples.

Development and analytical validation of a multivariate calibration method for determination of amoxicillin in suspension formulations by near infrared spectroscopy

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 65.0mgmL−1 of amoxicillin, providing a root mean square error of prediction (RMSEP) of 1.6mgmL−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.

Solid-State Digital Micro-Mirror Array Spectrometer for Hadamard Transform Measurements of Glucose and Lactate in Aqueous Solutions

A novel solid-state near-infrared spectrometer is presented based on a digital micro-mirror array device (DMD) that is well designed for Hadamard transform spectroscopy. This spectrometer is designed for the collection of transmission spectra over the C-H first overtone region of the near-infrared spectrum (6500-5500 cm(-1)). A spectral resolution of 2.2 nm (~11 cm(-1)) is realized by using a 25 μm diameter linear tungsten filament as the source. Such a thin filament reduces imaging aberrations into the micro-mirror array, thereby enhancing spectral resolution. After passing through the sample, the transmitted radiation is dispersed with a grating before being imaged onto the surface of the DMD. Hadamard transform masks are implemented through the DMD and the reflected light is monitored by a single-element photodiode detector. The analytical utility of this approach is demonstrated through the multivariate quantification of glucose and lactate in binary mixtures composed in an aqueous buffer solution. A signal-to-noise ratio of 35,000 is achieved through these aqueous samples, and the resulting quantitative measurements provide a standard error of prediction of 1.4 and 0.9 mM for glucose and lactate, respectively. The selectivity of the resulting calibration models is established by using both a pure component selectivity analysis as well as analysis of the net analyte signal for each component. These quantitative results from the DMD Hadamard transform spectrometer compare favorably to similar measurements performed with a commercial Fourier transform spectrometer.

Bismuth Modified Disposable Pencil‐Lead Electrode for Simultaneous Determination of 2‐Nitrophenol and 4‐Nitrophenol by Net Analyte Signal Standard Addition Method

AbstractA pencil‐lead electrode modified with a thin film of bismuth, that is “environmental friendlier” than mercury, was used for electrocatalytic reduction of 2‐nitrophenol (2‐NP) and 4‐nitrophenol (4‐NP) by differential pulse voltammetry and net analyte signal standard addition method (NASSAM). The modified electrode has electrocatalytic behavior toward reduction of 2‐NP and 4‐NP. Because of similar structures of analytes, at the modified electrode they have high overlapped signals that determination of them in the presence of each other is impossible with univariate methods. NASSAM is a very recently introduced method that is a new modification of the standard addition method, which was used for the simultaneous determination of 2‐NP and 4‐NP.

Simultaneous Determination of 6-Mercaptopurine and its Oxidative Metabolites in Synthetic Solutions and Human Plasma using Spectrophotometric Multivariate Calibration Methods.

6-Mercaptopurine (6MP) is an important chemotherapeutic drug in the conventional treatment of childhood acute lymphoblastic leukemia (ALL). It is catabolized to 6-thiouric acid (6TUA) through 8-hydroxo-6-mercaptopurine (8OH6MP) or 6-thioxanthine (6TX) intermediates. High-performance liquid chromatography (HPLC) is usually used to determine the contents of therapeutic drugs, metabolites and other important biomedical analytes in biological samples. In the present study, the multivariate calibration methods, partial least squares (PLS-1) and principle component regression (PCR) have been developed and validated for the simultaneous determination of 6MP and its oxidative metabolites (6TUA, 8OH6MP and 6TX) without analyte separation in spiked human plasma. Mixtures of 6MP, 8-8OH6MP, 6TX and 6TUA have been resolved by PLS-1 and PCR to their UV spectra. Recoveries (%) obtained for 6MP, 8-8OH6MP, 6TX and 6TUA were 94.5-97.5, 96.6-103.3, 95.1-96.9 and 93.4-95.8, respectively, using PLS-1 and 96.7-101.3, 96.2-98.8, 95.8-103.3 and 94.3-106.1, respectively, using PCR. The NAS (Net analyte signal) concept was used to calculate multivariate analytical figures of merit such as limit of detection (LOD), selectivity and sensitivity. The limit of detections for 6MP, 8-8OH6MP, 6TX and 6TUA were calculated to be 0.734, 0.439, 0.797 and 0.482 μmol L-1, respectively, using PLS and 0.724, 0.418, 0783 and 0.535 μmol L-1, respectively, using PCR. HPLC was also applied as a validation method for simultaneous determination of these thiopurines in the synthetic solutions and human plasma. Combination of spectroscopic techniques and chemometric methods (PLS and PCR) has provided a simple but powerful method for simultaneous analysis of multicomponent mixtures.

Application of Net Analyte Signal Standard Addition Method (NASSAM) for Simultaneous Determination of Lead and Tin by Differential Pulse Polarography

AbstractDifferential pulse polarography was used for simultaneous determination of Sn2+ and Pb2+. But there is a problem for simultaneous determination and it is high overlapped DPPs of mentioned cations that their determination is impossible in the presence of each other, so multivariate calibration methods as chemomatrics methods were used for this determination. There are some disadvantageous for multivariate calibration methods that can be solved by a new and simple method called net analyte signal standard addition method. This method has some advantages, such as: the use of a full voltammogram, realization in a single step, therefore it does not require calibration and prediction steps and only a few measurements are required for the determination.

Modified robust continuum regression by net analyte signal to improve prediction performance for data with outliers

Contaminated data exist in diverse situations, even in high quality surveys and experiments. If classical statistic models are blindly applied to data containing outliers, the results can be misleading at best. In this paper, a modified robust continuum regression (mRCR) method is proposed to improve prediction performance for data with outliers. The mRCR method constructs projection pursuit directions by using projection matrix for computing the net analyte signal (NAS) of the target analyte. This paper examines applications to the determination of glucose concentration by near-infrared (NIR) spectrometry, including aqueous solution with glucose experiment, plasma experiment in vitro, oral glucose tolerance test (OGTT) in vivo, to illustrate the advantages of mRCR for various kinds of outliers depending on the way of contamination. The results indicate that the mRCR method is entirely robust with respect to any type of outlying observations, and it yields smaller prediction errors for normal samples than other calibration methods.

Multivariate control charts based on net analyte signal (NAS) and Raman spectroscopy for quality control of carbamazepine

Raman spectroscopy and control charts based on the net analyte signal (NAS) were applied to polymorphic characterization of carbamazepine. Carbamazepine presents four polymorphic forms: I–IV (dihydrate). X-ray powder diffraction was used as a reference technique. The control charts were built generating three charts: the NAS chart that corresponds to the analyte of interest (form III in this case), the interference chart that corresponds to the contribution of other compounds in the sample and the residual chart that corresponds to nonsystematic variations. For each chart, statistical limits were developed using samples within the quality specifications. It was possible to identify the different polymorphic forms of carbamazepine present in pharmaceutical formulations. Thus, an alternative method for the quality monitoring of the carbamazepine polymorphic forms after the crystallization process is presented.

Simultaneous spectrophotometric determination of paracetamol and para‐aminophenol in pharmaceutical dosage forms using two novel multivariate standard addition methods based on net analyte signal and rank annihilation factor analysis

Recently we proposed two multivariate standard addition methods using net analyte signal concept and rank annihilation factor analysis, which we named SANAS and SARAF, respectively. These methods could model both indirect sample matrix effects and direct interference effects of the coexisting analytes. Here, the potential of these methods for simultaneous determination of paracetamol and para-aminophenol in the synthetic mixtures and pharmaceutical products was examined. It was found that both models could predict the concentration of analytes in synthetic mixtures with relative errors of prediction lower than 7%. Moreover, the employed methods exhibited the recoveries in the range of 93.11 and 108.67 for analysis of the drugs in the real matrices. From SANAS plots, the figures of merit including sensitivity, selectivity and limit of detection were calculated as 0.143 µg/ml, 0.587 and 0.018 µg/ml for paracetamol and 0.128 µg/ml, 0.547 and 0.020 µg/ml for para-aminophenol, respectively.

Development and Validation of a Multivariate Calibration Method for Determining Interfacial Tension of Transformers Insulating Oils by near Infrared Spectroscopy

The aim of this study was to develop and validate a multivariate calibration method based on partial least squares (PLS) and near infrared spectroscopy for determining the interfacial tension of insulating oils used in electricity power transformers. Forty-eighty oil samples were obtained from an electricity power company and were divided into a calibration set of 38 leaving 10 for the validation set. The reference values were measured with a ring tensiometer and ranged from 15 dyn cm−1 to 45 dyn cm−1. The spectra were registered from 1280 nm to 2500 nm and the best PLS model was selected with 10 latent variables, providing a root mean square error of prediction of 2 dyn cm−1 and a coefficient of determination between reference and predicted values of 0.962. This method was validated in the context of multivariate calibration and was considered to have adequate accuracy (prediction errors between −9% and 12%), precision and linearity. A bias test verified the absence of systematic errors in the model. A pseudo-univariate calibration curve was constructed based on the concept of net analyte signal. The proposed method was simple, rapid, non-destructive and considered appropriate for the routine use in a quality control laboratory of an electricity power company.

Simultaneous Determination of Antazoline and Naphazoline by the Net Analyte Signal Standard Addition Method and Spectrophotometric Technique

A novel net analyte signal standard addition method (NASSAM) was used for simultaneous determination of the drugs anthazoline and naphazoline. The NASSAM can be applied for determination of analytes in the presence of known interferents. The proposed method is used to eliminate the calibration and prediction steps of multivariate calibration methods; the determination is carried out in a single step for each analyte. The accuracy of the predictions against the H-point standard addition method is independent of the shape of the analyte and interferent spectra. The net analyte signal concept was also used to calculate multivariate analytical figures of merit, such as LOD, selectivity, and sensitivity. The method was successfully applied to the simultaneous determination of anthazoline and naphazoline in a commercial eye drop sample.

Spectrophotometric study of complex formation equilibria in the presence of interference using hard–soft net analyte signal method: Application to drug–metal complexation

In this article, the ability of a new and efficient hard–soft method, previously proposed by our research group, is reported for modeling of the complex formation equilibria in the presence of interferences. This method is based on the net analyte signal (NAS) concept, which is a part of total signal that is directly related to the concentration of the component of interest. It monitors the concentration changes of any chemical species involved in the evolutionary process without requiring any pure spectra or having previous knowledge about the presence of the interferences. The proposed hard–soft method based on net analyte signal (HS-NAS) only needs a chemical model for one of the species involved in the reaction under study. The reliability of the method was examined by applying it to the measured data and spectrum of the known real systems of Fe 2+–azithromycin and Ca 2+–tetracycline.

Multivariate control charts based on net analyte signal and near infrared spectroscopy for quality monitoring of Nimesulide in pharmaceutical formulations

Multivariate control charts based on the net analytical signal, in conjunction with near infrared spectroscopy, were developed to monitor the quality of a pharmaceutical formulation containing Nimesulide. Three control charts were developed: the NAS chart that corresponds to the analyte of interest (Nimesulide in this case), the interference chart that corresponds to the contribution of other compounds in the sample and the residual chart that corresponds to nonsystematic variation. From the limits estimated for each chart using samples inside the quality specifications, it was possible to identify the samples that were outside the specifications concerning Nimesulide concentration and to identify the presence of different constituents in the standard formulation.

Optical coefficient‐based multivariate calibration on near‐infrared spectroscopy

AbstractThe time and expense of calibration development limit the feasibility of NIR spectroscopy for many industrial applications, with a major portion of the costs being related to creation of a sufficient set of calibration samples. Net analyte signal (NAS) and generalized least squares (GLS) pre‐processing have been proposed in the literature as methods to simplify multivariate calibration by reducing the quantity of calibration samples by orthogonalizing or shrinking interference signals. Synthetic calibration has also been reported as a method to combine interference signals with pure component spectra to generate virtual calibration models, thereby reducing the number of real calibration samples required. The goals of this paper were to (1) compare theoretical and practical differences between NAS and GLS pre‐processing and (2) explore the potential of simplified NIR calibrations, both empirical and synthetic, constructed using optical coefficient‐based signal processing on predicting chemical compositions of pharmaceutical powder mixtures. A reduced calibration dataset including only one pharmaceutical powder mixture composition and pure component spectra was used for both empirical and synthetic calibrations. Absorption and reduced scattering coefficients, obtained from spatially‐resolved spectroscopy, were used herein as interference signals in NAS/GLS pre‐processing for both calibrations. As a result, NAS and GLS were shown to be equivalent in both theoretical and practical senses. After optical coefficient‐based signal processing, simplified calibrations, both empirical and synthetic, were demonstrated to have similar model performance as generic pre‐processing methods such as SNV and derivative, while requiring fewer principal components and achieving a lower prediction error. Copyright © 2010 John Wiley & Sons, Ltd.

Estimating the rate constant in second-order kinetics using hard-soft-net analyte signal (HS-NAS) method

Rank deficiency is the major problem associated with the chemometrics modeling of the second-order chemical reactions of the form of A + B → C. In this article, the application of the hard-soft-net analyte signal (HS-NAS), as a newly proposed method in our research group, is described for modeling of second-order reactions. This combined hard-soft method is based on the net analyte signal (NAS) concept, which is defined as a part of total signal that is directly related to the concentration of the component of interest. Therefore, concentration changes versus time can be obtained by calculating NAS for any chemical species involved in the reaction without requiring any pure component spectra or extra runs. The power of the method was verified by applying it to the resolution of simulated data sets containing noises added at different levels. The resolution of the second-order reaction between amoxicillin and 1, 2-naphthoqoinone was also tested as a real chemical system.

Net analyte signal based two-dimensional (NAS 2D) correlation near infrared spectroscopy

A new method of analysis, based on the net analyte signal presented by Lorber is proposed for the two-dimensional correlation near infrared spectroscopy. A spectra data set under the static perturbation of concentration was collected. NAS is manipulated for removing the information that was unrelated to a certain analyte. To demonstrate the potential of NAS 2D correlation spectroscopy, a set of concentration-dependent near infrared spectra of Sinomenine Hydrochloride in methanol was used as an example. The results show that NAS 2D, reconstructed from a series of principal factors can extract more subtle and useful spectra features, and make the band assignment explicable for structure analysis.

Quantitative analysis of mixed hydrofluoric and nitric acids using Raman spectroscopy with partial least squares regression

Mixed hydrofluoric and nitric acids are widely used as a good etchant for the pickling process of stainless steels. The cost reduction and the procedure optimization in the manufacturing process can be facilitated by optically detecting the concentration of the mixed acids. In this work, we developed a novel method which allows us to obtain the concentrations of hydrofluoric acid (HF) and nitric acid (HNO(3)) mixture samples with high accuracy. The experiments were carried out for the mixed acids which consist of the HF (0.5-3wt%) and the HNO(3) (2-12wt%) at room temperature. Fourier Transform Raman spectroscopy has been utilized to measure the concentration of the mixed acids HF and HNO(3), because the mixture sample has several strong Raman bands caused by the vibrational mode of each acid in this spectrum. The calibration of spectral data has been performed using the partial least squares regression method which is ideal for local range data treatment. Several figures of merit (FOM) were calculated using the concept of net analyte signal (NAS) to evaluate performance of our methodology.