Application of multivariate self-modeling curve resolution to the quantitation of trace levels of organophosphorus pesticides in natural waters from interlaboratory studies

Exploring band-free Raman microspectrometry combined with PCA and MCR-ALS for size-resolved forensic analysis of uranium in aerosols in a model nuclear atmosphere

Achieving non-destructive micrometer-scale molecular and structural analysis of uranic materials in atmospheric aerosols with traditional methodologies is a challenge. Spatially resolved analysis of uranium in actinide-bearing aerosols is critical for nuclear forensics. Although laser Raman microspectrometry enables this, for the normally low uranium concentrations in the aerosols the spectra are indiscernible (band-free) against pronounced background: trace analysis requires a push in analytical strategy. We combined laser Raman microspectrometry (utilizing two lasers (λ = 532 nm, λ = 785 nm)) with principal component analysis (PCA) and multivariate curve resolution-alternate least squares (MCR-ALS) to perform size-resolved analysis of uranium in aerosols. Uranium-specific Raman scatter bands corresponding to uranyl nitrate (860 cm-1), uranium sulphate (868 cm-1), uranyl chloride (816 cm-1) and uranium trioxide (839 cm-1) were detected. The 816 cm-1, 854 cm-1, 868 cm-1 bands were resolved by MCR-ALS and used to identify and map uranium in PM4.5 size aerosols. Based on spectral feature selection of the signature bands, PCA identified two sources of aerosol particles in model nuclear atmosphere - Sea spray for PM4.5 and re-suspension of 'nuclear' dust from a rare earth element (REE) mine for PM2.5. The MCR-ALS-resolved uranium bands showed the potential for attributive nuclear forensic analysis.

Liquid chromatography coupled with photodiode array and a multivariate curve resolution - Alternating least square algorithm for identification and quantification of co-eluting impurities in pharmaceutical analysis

This paper systematically investigated and reported for the first time the identification and quantification of co-eluting impurities as low as 0.05 area% by PDA with i-PDeA II deconvolution software in the LabSolutions Chromatographic Data System (CDS) using an integrated multivariate curve resolution-alternating least squares (MCR-ALS) algorithm with a bidirectional exponentially modified Gaussian (BEMG) model function. The algorithm was able to consistently identify 0.05% impurities when co-eluting with the main component (Rs ≥ 0.8) as well as when co-eluting with another impurity (Rs ≥ 0.5). In the case of two co-eluting impurities from 0.05% to 1% (Rs ≥ 0.5), the quantification error ranged from +10.6% to -16.7%. In the case of an impurity co-eluting with the main component (Rs ≥ 0.8), the quantification error was 4.4-8.9% for 1% impurity and 109-184% for 0.05% impurity. The precision was excellent for the range of 0.05-1.0% impurities with the RSD being 1.4-3.0% for 1% impurity and 4.0-8.7% for 0.05% impurity. The identification rate and quantitation accuracy were not affected by the spectral similarity of the molecules, as comparable results were obtained by analyzing two molecules with low similarity (4,4-difluorobenzophenone and valerophenone) and two molecules with high similarity (diazepam and oxazepam) based on simulated data. This peak resolution by MCR-ALS approach provides fast and robust identification and quantification of co-eluting impurities even when method development efforts do not provide complete separation of the target peaks, and could therefore find a wide range of applications in pharmaceutical and other types of analyses.

Micro-Raman Spectroscopy and X-ray Diffraction Analyses of the Core and Shell Compartments of an Iron-Rich Fulgurite

Fulgurites are naturally occurring structures that are formed when lightning discharges reach the ground. In this investigation, the mineralogical compositions of core and shell compartments of a rare, iron-rich fulgurite from the Mongolian Gobi Desert were investigated by X-ray diffraction and micro-Raman spectroscopy. The interpretation of the Raman data was helped by chemometric analysis, using both multivariate curve resolution (MCR) and principal component analysis (PCA), which allowed for the fast identification of the minerals present in each region of the fulgurite. In the core of the fulgurite, quartz, microcline, albite, hematite, and barite were first identified based on the Raman spectroscopy and chemometrics analyses. In contrast, in the shell compartment of the fulgurite, the detected minerals were quartz, a mixture of the K-feldspars orthoclase and microcline, albite, hematite, and goethite. The Raman spectroscopy results were confirmed by X-ray diffraction analysis of powdered samples of the two fulgurite regions, and are consistent with infrared spectroscopy data, being also in agreement with the petrographic analysis of the fulgurite, including scanning electron microscopy with backscattering electrons (SEM-BSE) and scanning electron microscopy with energy dispersive X-ray (SEM-EDX) data. The observed differences in the mineralogical composition of the core and shell regions of the studied fulgurite can be explained by taking into account the effects of both the diffusion of the melted material to the periphery of the fulgurite following the lightning and the faster cooling at the external shell region, together with the differential properties of the various minerals. The heavier materials diffused slower, leading to the concentration in the core of the fulgurite of the iron and barium containing minerals, hematite, and barite. They first underwent subsequent partial transformation into goethite due to meteoric water within the shell of the fulgurite. The faster cooling of the shell region kinetically trapped orthoclase, while the slower cooling in the core area allowed for the extensive formation of microcline, a lower temperature polymorph of orthoclase, thus justifying the prevalence of microcline in the core and a mixture of the two polymorphs in the shell. The total amount of the K-feldspars decreases only slightly in the shell, while quartz and albite appeared in somewhat larger amounts in this compartment of the fulgurite. On the other hand, at the surface of the fulgurite, barite could not be stabilized due to sulfate lost (in the form of SO₂ plus O₂ gaseous products). The conjugation of the performed Raman spectroscopy experiments with the chemometrics analysis (PCA and, in particular, MCR analyses) was shown to allow for the fast identification of the minerals present in the two compartments (shell and core) of the sample. This way, the XRD experiments could be done while knowing in advance the minerals that were present in the samples, strongly facilitating the data analysis, which for compositionally complex samples, such as that studied in the present investigation, would have been very much challenging, if possible.

Spatial Profiling of a Pd/Al2O3 Catalyst during Selective Ammonia Oxidation

The utilization of operando spectroscopy has allowed us to watch the dynamic nature of supported metal nanoparticles. However, the realization that subtle changes to environmental conditions affect the form of the catalyst necessitates that we assess the structure of the catalyst across the reactant/product gradient that exists across a fixed bed reactor. In this study, we have performed spatial profiling of a Pd/Al₂O₃ catalyst during NH₃ oxidation, simultaneously collecting mass spectrometry and X-ray absorption spectroscopy data at discrete axial positions along the length of the catalyst bed. The spatial analysis has provided unique insights into the structure–activity relationships that govern selective NH₃ oxidation—(i) our data is consistent with the presence of PdN_x after the spectroscopic signatures for bulk PdN_x disappear and that there is a direct correlation to the presence of this structure and the selectivity toward N₂; (ii) at high temperatures, ≥400 °C, we propose that there are two simultaneous reaction pathways—the oxidation of NH₃ to NO_x by PdO and the subsequent catalytic reduction of NO_x by NH₃ to produce N₂. The results in this study confirm the structural and catalytic diversity that exists during catalysis and the need for such an understanding if improvements to important emission control technologies, such as the selective catalytic oxidation of NH₃, are to be made.

Soft-trilinear constraints for improved quantitation in multivariate curve resolution

Soft trilinearity constraints give a range of feasible solutions (grey) that envelop the true solution (blue). PARAFAC2 (green) and MCR-ALS results (black) are shown for comparison.

Study on the Visualization of Pigment in Haematococcus pluvialis by Raman Spectroscopy Technique

As an ideal raw material for the production of astaxanthin, H. pluvialis was drawing attention during the last few years, there are some research topics initiated to find out the synthetic pathway of astaxanthin in H. pluvialis. In this study, confocal microscopic Raman technology was utilized to analyze the point-by-point mapping for H. pluvialis, and the visualization of pigment such as carotenoid and astaxanthin content were achieved. By comparing the Raman spectra of H. pluvialis and standard product of astaxanthin, and using the C = C stretching vibration of the Raman intensity as the main indicator for carotenoids, the visual spatial distribution for the carotenoids content was obtained. The MCR-ALS was applied to analyze the Raman data of H. pluvialis, and the information of astaxanthin was extracted to achieve real-time spatial distribution. The visualization of astaxanthin content shows that MCR-ALS is very effective for extracting the information of astaxanthin content from H. pluvialis. By exploring the spatial distribution of carotenoids and astaxanthin contents, analyzing the spatial distribution rules during its growth, Raman spectroscopy technology can be utilized to investigate the internal components of the pigment (ataxanthin, etc.) in H. pluvialis, which make it as an effective methodology to monitor the accumulation and changing mechanism of pigment content in microalgae.

Band target entropy minimization and target partial least squares for spectral recovery and quantitation

The resolution and quantitation of pure spectra of minority components in measurements of chemical mixtures without prior knowledge of the mixture is a challenging problem. In this work, a combination of band target entropy minimization (BTEM) and target partial least squares (T-PLS) was used to obtain estimates for single pure component spectra and to calibrate those estimates in a true, one-at-a-time fashion. This approach allows for minor components to be targeted and their relative amounts estimated in the presence of other varying components in spectral data. The use of T-PLS estimation is an improvement to the BTEM method because it overcomes the need to identify all of the pure components prior to estimation. Estimated amounts from this combination were found to be similar to those obtained from a standard method, multivariate curve resolution-alternating least squares (MCR-ALS), on a simple, three component mixture dataset. Studies from two experimental datasets demonstrate where the combination of BTEM and T-PLS was used to model the pure component spectra and to obtain concentration profiles of minor components, but MCR-ALS could not.

Enhanced target factor analysis

Target testing or target factor analysis, TFA, is a well-established soft analysis method. TFA answers the question whether an independent target test vector measured at the same wavelengths as the collection of spectra in a data matrix can be excluded as the spectrum of one of the components in the system under investigation. Essentially, TFA cannot positively prove that a particular test spectrum is the true spectrum of one of the components, it can, only reject a spectrum. However, TFA will not reject, or in other words TFA will accept, many spectra which cannot be component spectra. Enhanced Target Factor Analysis, ETFA addresses the above problem. Compared with traditional TFA, ETFA results in a significantly narrower range of positive results, i.e. the chance of a false positive test result is dramatically reduced. ETFA is based on feasibility testing as described in Refs. [16-19]. The method has been tested and validated with computer generated and real data sets.

An improved independent component analysis model for 3D chromatogram separation and its solution by multi-areas genetic algorithm

Background

The 3D chromatogram generated by High Performance Liquid Chromatography-Diode Array Detector (HPLC-DAD) has been researched widely in the field of herbal medicine, grape wine, agriculture, petroleum and so on. Currently, most of the methods used for separating a 3D chromatogram need to know the compounds' number in advance, which could be impossible especially when the compounds are complex or white noise exist. New method which extracts compounds from 3D chromatogram directly is needed.

Methods

In this paper, a new separation model named parallel Independent Component Analysis constrained by Reference Curve (pICARC) was proposed to transform the separation problem to a multi-parameter optimization issue. It was not necessary to know the number of compounds in the optimization. In order to find all the solutions, an algorithm named multi-areas Genetic Algorithm (mGA) was proposed, where multiple areas of candidate solutions were constructed according to the fitness and distances among the chromosomes.

Results

Simulations and experiments on a real life HPLC-DAD data set were used to demonstrate our method and its effectiveness. Through simulations, it can be seen that our method can separate 3D chromatogram to chromatogram peaks and spectra successfully even when they severely overlapped. It is also shown by the experiments that our method is effective to solve real HPLC-DAD data set.

Conclusions

Our method can separate 3D chromatogram successfully without knowing the compounds' number in advance, which is fast and effective.

A Decomposition Model for HPLC-DAD Data Set and Its Solution by Particle Swarm Optimization

This paper proposes a separation method, based on the model of Generalized Reference Curve Measurement and the algorithm of Particle Swarm Optimization (GRCM-PSO), for the High Performance Liquid Chromatography with Diode Array Detection (HPLC-DAD) data set. Firstly, initial parameters are generated to construct reference curves for the chromatogram peaks of the compounds based on its physical principle. Then, a General Reference Curve Measurement (GRCM) model is designed to transform these parameters to scalar values, which indicate the fitness for all parameters. Thirdly, rough solutions are found by searching individual target for every parameter, and reinitialization only around these rough solutions is executed. Then, the Particle Swarm Optimization (PSO) algorithm is adopted to obtain the optimal parameters by minimizing the fitness of these new parameters given by the GRCM model. Finally, spectra for the compounds are estimated based on the optimal parameters and the HPLC-DAD data set. Through simulations and experiments, following conclusions are drawn: (1) the GRCM-PSO method can separate the chromatogram peaks and spectra from the HPLC-DAD data set without knowing the number of the compounds in advance even when severe overlap and white noise exist; (2) the GRCM-PSO method is able to handle the real HPLC-DAD data set.

Chromatographic fingerprinting and related chemometric techniques for quality control of traditional Chinese medicines

Development of chromatographic fingerprint (CF) and related chemometric methods and their applications to quality control of traditional Chinese medicines (TCMs) were discussed. CF is essentially a kind of quality control method for TCMs (or Chinese herbal medicines). Also, it is a quality-relevant-data high-throughput and integral tool to explore chemically the complexity of TCMs. With the help of chemometrics, some difficulties in evaluation and analysis of CFs, such as calculation of information content, peak alignment, pattern analysis, deconvolution of overlapping peaks, etc. could be well solved. To further explore TCMs synergic quality, intensive study of CF coupled with chemometrics will create the possibility to achieve the aim to reveal the working mechanisms of TCMs and to further control and strengthen TCMs' intrinsic quality in a comprehensive manner.

Extraction of chemical information from complex analytical signals by a non-negative independent component analysis

Extraction of chemical information of the components from a complex analytical signal has been a great challenge in chemometrical studies for complex sample analysis. Independent component analysis (ICA) has been widely applied in complex signal separation, including the multicomponent overlapping signals in analytical chemistry. Difficulties, however, still exist in the application of ICA in chemical signal processing because chemical signals of different components are generally correlated and non-negative, instead of independence as hypothesized in ICA. In this study, a non-negative ICA method is proposed by means of a post rotation of the independent components (ICs) and applied to the extraction of the chemical information of the components from the signals of complex samples. Raman spectra of pharmaceutical tablets and gas chromatography-mass spectrometry (GC-MS) data of cigarette smoke are qualitatively analyzed. The results show that the Raman spectrum of the active substance in the pharmaceutical tablets and the mass spectra of the components in the overlapping GC-MS signal can be effectively and accurately extracted by using the proposed method.

Quantitative determination in chromatographic analysis based on n-way calibration strategies

Chemometric techniques for calibration with three-way signals are sufficiently developed for their use in routine analysis. The advantage of the second order property (the possibility of quantifying an analyte in the presence of interferents) together with the guarantee of the uniqueness of the decomposition, what means to extract the signal corresponding only to the analyte of interest, make these calibration techniques especially useful for the quantification and identification of analytes in complex samples. This has a particular interest in the identification and quantification of banned substances or substances with a specified maximum limit. The paper describes the theory of the calibration methodology in relation to the signal order and then focuses the analysis on the three-way techniques commonly used in calibration: n-way partial least squares, multivariate curve resolution and parallel factor analysis. The figures of merit needed for the accreditation of analytical methods are analyzed from the viewpoint of n-way calibrations in chromatography.

Factor analysis of hyphenated chromatographic data

Factor analysis (FA) is a family of widely used methods to obtain the underlying sources of variation of data tables. Typically, hyphenated chromatographic data provide data tables with one elution direction and another linked to the detector response. In this context, the factors are the eluting compounds and the profiles defining each factor are the elution profile and the pure response of the compound. This article describes the use of FA in chromatography through diverse tools and problems. Examples of determination of number of compounds, peak purity problems, resolution of overlapped compounds or extension to simultaneous analysis of multiple runs (higher-order data structures) to obtain qualitative and quantitative information are reviewed.

Alternative calibration approaches for LC–MS quantitative determination of coeluted compounds in complex environmental mixtures using multivariate curve resolution

Different calibration approaches including external calibration, standard addition and internal standard are evaluated for quantification of coeluted compounds in liquid chromatography with MS spectrometry detection in scan mode and using multivariate curve resolution. These different calibration approaches are proposed to cope with sensitivity changes and matrix effects encountered in the analysis of complex natural environmental samples. By using them, multivariate curve resolution analysis of MS data in scan mode gave similar quantitative results to those obtained by LC-MS in selected ion monitoring (SIM) mode (in both cases errors were below 16% for internal standard combined with standard addition strategy), and it provided at the same time a means of analyte confirmation via their resolved pure MS spectra, and a means to gather a larger amount of information about the whole chromatographic process and to facilitate the simultaneous determination of multiple analytes in the same chromatographic run using the same experimental and instrumental conditions.

Analysis of environmental samples by application of multivariate curve resolution on fused high-performance liquid chromatography–diode array detection mass spectrometry data

Multivariate curve resolution-alternating least squares (MCR-ALS) is applied to solve coelution problems in liquid chromatograpy with diode array detection (DAD) and mass spectrometry (MS). Fusion of DAD and MS detector signals improved results versus those obtained using only one of the two detector signals. Application of wavelet transform to MS data before its fusion with DAD data, further help to facilitate the resolution and quantitation of the coeluted compounds under study, besides a decrease of time of analysis. Mixtures of biocide compounds in standard mixtures and in environmental samples (sediment and wastewater samples) were analyzed with estimated quantitation errors below 12%.

Alternative moving window factor analysis for comparison analysis between complex chromatographic data

In this investigation, a novel chemometric method is developed for the analysis of five possible relationships of components or spectral features between two correlative but different hyphenated chromatographic systems. It is very helpful for comparison study of components present in different complex systems in both chemistry and systems biology. The proposed method, named alternative moving window factor analysis (AMWFA), could be utilized to determine the number of common components between different samples and then to identify their corresponding spectra half-automatically. AMWFA can alternatively be employed to mind for the selective information hiding in anyone of the two compared data X and Y, and to self-verify the resolution results by changing the extracted target matrices in analysis. From the results of comparison of simulated hyphenated chromatographic data, volatile chemical components in drug pair rhizoma ligustici chuanxiong-radix paeoniae rubra (RLC-RPR) and its single herbal medicines, and analysis of Angelica oral solution and its plasma sample after oral intake to rabbit, powerful ability of the proposed method is shown.

Determination of pesticides by solid phase extraction followed by gas chromatography with nitrogen–phosphorous detection in natural water and comparison with solvent drop microextraction

The European Union specifies that drinking water can contain pesticide residues at concentrations of up to 0.1 microg/L each and 0.5 microg/L in total, and that 1-3 microg/L of pesticides can be present in surface water, but the general idea is to keep discharges, emissions and losses of priority hazardous substances close to zero for synthetic substances. Therefore, in order to monitor pesticide levels in water, analytical methods with low quantification limits are required. The method proposed here is based on solid phase extraction (SPE) followed by gas chromatography with a nitrogen-phosphorous detector (GC-NPD). During method development, six organophosphate pesticides (azinphos-ethyl, chlorfenvinphos, chlorpyriphos, ethoprophos, fenamiphos and malathion) and two organonitrogen pesticides (alachlor and deltamethrin) were considered as target analytes. Elution conditions that could influence the efficiency of the SPE were studied. The optimized methodology exhibited good linearity, with determination coefficients of better than 0.996. The analytical recovery for the target analytes ranged from 70 to 100%, while the within-day precision was 4.0-11.5%. The data also showed that the nature of the aqueous matrice (ultrapure, surface or drinking water) had no significant effect on the recovery. The quantification limits for the analytes were found to be 0.01-0.13 microg/L (except for deltamethrin, which was 1.0 microg/L). The present methodology is easy, rapid and gives better sensitivity than solvent drop microextraction for the determination of organonitrogen and organophosphate pesticides in drinking water at levels associated with the legislation.

Solving liquid chromatography mass spectrometry coelution problems in the analysis of environmental samples by multivariate curve resolution

Multivariate curve resolution-alternating least squares (MCR-ALS) is shown to be a powerful tool to resolve coelution problems in liquid chromatograpy-mass spectrometry (LC-MS) in scan mode. This investigation was performed using two types of LC columns, one traditional LC column of 25 cm length with a slow gradient and a shorter LC column of 7.5 cm with a rapid gradient which allowed much faster analysis and save of reagents and solvents. Mixtures of multiple biocide compounds were simultaneously analyzed in standard mixtures and in environmental samples (sediment and wastewater samples) with little sample pretreatment. Using the more traditional LC 25 cm column, all biocide compounds were properly resolved by MCR-ALS and quantitatively analyzed with estimated errors always below 20%. When fast chromatography (LC column of 7.5 cm) was used, MCR-ALS resolution of the more strongly coeluted compounds was also achieved but limitations were found in their simultaneous quantitative determination, specially for environmental samples.

Determination of parathion residues in rice samples using a flow injection chemiluminescence method

A sensitive flow injection chemiluminescence method is described for the determination of parathion pesticide, based upon its direct chemiluminescence reaction with luminol and hydrogen peroxide in the presence of non-ionic surfactant polyethylene glycol 400. Under the selected experimental conditions, the concentration of parathion is proportional to the CL intensity in the range 0.02-1.0 mg/L. The detection limit was 0.008 mg/L and the relative standard deviation was 2.8% for 0.2 mg/L parathion solution (n = 11). This method was successfully applied to the determination of parathion residue in rice samples.

Continuous solid-phase extraction and gas chromatographic determination of organophosphorus pesticides in natural and drinking waters

A simple, rapid continuous-flow solid-phase extraction method with gas chromatographic detection for the determination of organophosphorus pesticides is proposed. The continuous system consists of an adsorbent column where pesticides are preconcentrated and subsequently eluted with ethyl acetate. Various sorbent materials were assayed of which RP-C18 was found to provide the best results, with a sorption efficiency close to 100%. A comparative study of the determination of pesticides in aqueous samples was conducted using gas chromatography with nitrogen-phosphorus (NPD) and flame ionization (FID) detection. The detection limits of the method for 10 ml of sample were between 50-130 ng/l and 4.5-1 1.7 microg/l with NPD and FID detection, respectively. The method was used to determine organophosphorus pesticides in river, pond, well and tap waters, all with good precision (2.9-4.3%) and recoveries ranging from 93.8 to 104.5%.

Monitoring of the pesticide diazinon in soil, stem and surface water of rice fields

Diazinon is an organophosphorus insecticide (OPP) that is used as a pesticide for Chilo suppressalis (WLK) (Lep., Pyralidae) in rice fields. The extraction of diazinon from soil and the stems of rice plants has been carried out by microwave-assisted extraction (MAE) and the results compared with ultrasonic extraction (USE). The best parameters for MAE are hexane-acetone (8:2 v/v) as a solvent, a 2.5 min extraction time, and 20 ml of the solvent volume. Also, surface-water samples of the rice fields were extracted by solid phase extraction (SPE) using a C18 disc. The optimum conditions of SPE were a sample volume of 750 ml, a pH of 7 and high ionic strength of water. The extracted samples were analyzed by gas chromatography-mass spectrometry (GC-MS). The relative standard deviation (RSD) and regression coefficients related to the linearity were <3.5% (n = 5) and 0.99, respectively. The limit of detection (LOD) is 0.1 ng ml(-1) with selected ion monitoring (SIM) at 137 m/z. The average recoveries of diazinon in soil and stem samples by MAE and surface-water by SPE were 98% (+/-3), 94% (+/-5) and 87% (+/-3), respectively. In June, the concentration of diazinon in soil and stem samples of the rice plants in Guilan province is high (55 ng ml(-1)) and in September is low (2 ng ml(-1)). In surface-water samples, the results are converse. In November, diazinon can not be detected in soil, stem or surface-water samples. Diazinon is degraded to diethylthiophosphoric acid. Also, three microorganism genera (Pseudomonas sp, Flavobacterium sp and Agrobacterium sp) have been found to degrade diazinon in soil and surface water.

Determination of ebrotidine metabolites in overlapping peaks from capillary zone electrophoresis using chemometric methods

This paper illustrates the possibilities of chemometric methods in the resolution and quantification of various compounds in overlapping peaks from capillary electrophoresis. Ebrotidine and most of its metabolites were efficiently separated by capillary zone electrophoresis (CZE) in a fused-silica capillary. However, the procedure was not suitable for the physical separation of the three less ionizable metabolites, which comigrated and overlapped with the electroosmotic flow signal. Multivariate curve resolution based on an alternating least squares procedure was used for their mathematical resolution. For such a purpose, data obtained in the CZE system with a diode array detector, which consisted of UV spectra registered over time, were analyzed. The ebrotidine metabolites were successfully resolved and quantified in synthetic mixtures and urine samples.

Determination of amino acids in overlapped capillary electrophoresis peaks by means of partial least-squares regression

Amino acid derivatives of 1,2-naphthoquinone-4-sulfonate (NQS) can be separated by capillary electrophoresis at 30 kV in a fused-silica capillary by using a 40 mM sodium tetraborate-isopropanol (3:1, v/v) solution as background electrolyte. This procedure was suitable for the most common amino acids. However, the peaks of three amino acids (phenylalanine, isoleucine and tyrosine) were only partially resolved and peaks of histidine and leucine derivatives overlapped completely. Partial least-squares regression (PLS) may overcome the lack of selectivity for these amino acids. Spectroelectropherograms of the corresponding amino acid derivative peaks were monitored with a diode-array spectrophotometer in the range 225 to 540 nm. Both spectra and electropherograms can be used as multivariate data for further analysis. In general, the best predictions were obtained using the time domain.

Resolution of overlapped peaks of amino acid derivatives in capillary electrophoresis using multivariate curve resolution based on alternating least squares

The application of chemometric techniques to the resolution of overlapped peaks in capillary electrophoresis (CE) is described. When a physical separation can not be completely accomplished, chemometrics might still resolve the determination of the analytes mathematically. CE with diode array detection can provide a large amount of data consisting of spectra registered over time. In this study, the capillary electrophoretic separation of 1,2-naphthoquinone-4-sulfonate derivatives of amino acids is studied. Most of the common amino acid derivatives can be separated at 30 kV in a fused-silica capillary by using a 40 mM sodium tetraborate + isopropanol (3:1 v/v) solution as background electrolyte. However, peaks of certain derivatives (Phe, His, Leu and Ile) still overlap. A multivariate curve resolution method based on an alternating least squares optimization procedure is used for the resolution of the overlapped electrophoretic peaks. The method takes advantage of spectral and electrophoretic differences of analytes to recover their pure electrophoretic and spectral profiles. In addition, each analyte in the mixture can be quantified using the corresponding standards.

Generalised H-point standard addition method for the isolation of the analyte signal from the sample signal when coelution of unknown compounds occurs in liquid chromatography

The generalised H-point standard addition method (GHPSAM) is proposed for isolating the analytical signal of an analyte from the signal of an unknown sample. Samples containing two and three coeluting compounds have been analysed. The accuracy of the predictions depends on the shape of the analyte and interferent spectra but not on the degree of chromatographic overlap. This methodology involves the location of linear intervals for the unknown interference spectrum from the spectrum of the sample. Once the linear interval has been found the selection of three wavelengths within the interval will allow the cancellation of the signal of the unknown interferent. The method has been applied to the determination of diuretics, amphetamines and phenols in water.

Development of monoclonal ELISAs for azinphos-methyl. 2. Assay optimization and water sample analysis

Two enzyme-linked immunosorbent assays (ELISA) for the insecticide azinphos-methyl have been optimized and characterized. Both ELISAs are based on monoclonal antibodies produced from an immunogen with a hapten containing a phthalimido moiety and on protein conjugates of heterologous ligands containing a 1,2,3-benzotriazine group. Assay I was performed in the conjugate-coated ELISA format and assay II in the antibody-coated format. Several physicochemical factors (ionic strength, pH, incubation times, and Tween 20 and BSA concentrations) that influence assay performance were studied and optimized. Regarding specificity, both monoclonal immunoassays highly cross-reacted with azinphos-ethyl and phosmet. Finally, both assays were applied to the analysis of azinphos-methyl in spiked real water samples. For assay I the sensitivity, estimated as the I(50) value, was 0.40 nM, with a practical working range between 0.10 and 1.75 ng/mL and a limit of detection of 0.05 ng/mL. For assay II the sensitivity was 1.01 nM, with a practical working range between 0.32 and 2.54 ng/mL and a limit of detection of 0.08 ng/mL.

Multivariate curve resolution: a possible tool in the detection of intermediate structures in protein folding

Different multivariate data analysis techniques based on factor analysis and multivariate curve resolution are shown for the study of biochemical evolutionary processes like conformational changes and protein folding. Several simulated CD spectral data sets describing different hypothetical protein folding pathways are analyzed and discussed in relation to the feasibility of factor analysis techniques to detect and resolve the number of components needed to explain the evolution of the CD spectra corresponding to the process (i.e., to detect the presence of intermediate forms). When more than two components (the native and unordered forms) are needed to explain the evolution of the spectra, an iterative multivariate curve resolution procedure based on an alternating least squares algorithm is proposed to estimate the CD spectrum corresponding to the intermediate form.