Fluorescence determination of metoprolol in human plasma by trilinear decomposition-based calibration techniques

In this study a new spectrofluorimetric method for the direct determination of metoprolol in human plasma is presented and discussed. It is based on the use of fluorescence excitation–emission matrices (EEMs) and second-order calibration performed with parallel factor analysis (PARAFAC) or alternating trilinear decomposition (ATLD). This methodology enables accurate and reliable discrimination of the analyte signal, even in the presence of unknown and uncalibrated fluorescent component(s), which is often referred to as the second-order advantage. No separation or sample pretreatment steps were required. Satisfactory results were obtained. Metoprolol recoveries in plasma were determined as 87±2% and 90±4% with PARAFAC and ATLD, respectively. All RSD values of intra- and interday assays were below 5%. Figure A three-dimensional plot of EEMs for a plasma sample and metoprolol solution     

Determination of the titanium content of human transferrin by inductively-coupled plasma-atomic-emission spectroscopy

We report a simple method that combines dialysis, as a purification method, with the multielement capability of ICP to determine the titanium-to-transferrin mole ratio at physiological pH, under buffer conditions. The method, by means of which titanium and transferrin are determined simultaneously, enabled us to assess the binding capacities of different titanocene complexes. Figure Titanocene dichloride     

Estimating the chemical rank of three-way data arrays by a simple linear transform incorporating Monte Carlo simulation

Estimating an appropriate chemical rank of a three-way data array is very important to second-order calibration. In this paper, a simple linear transform incorporating Monte Carlo simulation approach (LTMC) to estimate the chemical rank of a three-way data array was suggested. The new method determines the chemical rank through performing a simple linear transform procedure on the original cube matrix to produce two subspaces by singular value decomposition. One of two subspaces is derived from the original three-way data array itself and the other is derived from a new three-way data array produced by the linear transformation of the original one. Projection technique incorporating the Monte Carlo approach acts as distinguishing criterion to choose the appropriate component number of the system. Simulated three-way trilinear data arrays with different noise types (homoscedastic and heteroscedastic), various noise level as well as high collinearity are used to illustrate the feasibility of the new method. The results have shown that the new method could yield accurate results with different conditions appended. The feasibility of the new method is also confirmed by two real arrays, HPLC-DAD data and excitation-emission fluorescent data. All the results are compared with the other three factor-determining methods: factor indicator function (IND), core consistency diagnostic (CORCONDIA) and two-mode subspace comparison (TMSC) approach. It shows that the newly proposed algorithm can objectively and quickly determine the chemical rank to fit the trilinear model.     

Analysis of biosensors by chemically specific optical techniques. Chemiluminescence-imaging and infrared spectroscopic mapping ellipsometry

The standard methods currently used to read out microarrays are fluorescent and chemiluminesent imaging techniques. These methods require labeling of a component with a marker and, usually, only the concentration of the marker molecule is detected. A label-free imaging method that also enables quantitative spectroscopic analysis of the composition and component interaction would be of great advantage. In this article it is shown for the first time that IR mapping ellipsometry enables label-free imaging of a biochip before and after incubation with peptide solution. The measurements prove that IR ellipsometry is a sensitive tool for laterally resolved identification of the different materials and determination of the composition of a biochip. The lateral resolution required was achieved by using radiation from an infrared synchrotron beamline.      

SPME in environmental analysis

Recent advances in the use of solid-phase microextraction (SPME) in environmental analysis, including fiber coatings, derivatization techniques, and in-tube SPME, are reviewed in this article. Several calibration methods for SPME, including traditional calibration methods, the equilibrium extraction method, the exhaustive extraction method, and several diffusion-based calibration methods, are presented. Recent developed SPME devices for on-site sampling and several applications of SPME in environmental analysis are also introduced.      

Resolution of overlapping signals in spectrometry using a wavelet packet transform and an Elman recurrent neural network

A novel method named a wavelet packet transform based Elman recurrent neural network (WPTERNN) was proposed for the simultaneous UV–visible spectrometric determination of Cu(II), Cd(II) and Zn(II). This method combined wavelet packet denoising with an Elman recurrent neural network. A wavelet packet transform was applied to perform data compression, to extract relevant information, and to eliminate noise and collinearity. An Elman recurrent network was applied for nonlinear multivariate calibration. In this case, using trials, the kind of wavelet function, the decomposition level, and the number of hidden nodes for the WPTERNN method were selected as Daubechies 14, 3, and 8, respectively. A program (PWPTERNN) was designed that could perform the simultaneous determination of Cu(II), Cd(II) and Zn(II). The relative standard errors of prediction (RSEP) obtained for all components using WPTERNN, a Elman recurrent neural network (ERNN), partial least squares (PLS), principal component regression (PCR), Fourier transform based PCR (FTPCR), and multivariate linear regression (MLR) were compared. Experimental results demonstrated that the WPTERRN method was successful even where there was severe overlap of spectra. The results obtained from an additional test case also demonstrated that the WPTERNN method performed very well. Figure The part of WP coefficients obtained by wavelet packet transforms     

A linear modulation-based stochastic resonance algorithm applied to the detection of weak chromatographic peaks

A simple stochastic resonance algorithm based on linear modulation was developed to amplify and detect weak chromatographic peaks. The output chromatographic peak is often distorted when using the traditional stochastic resonance algorithm due to the presence of high levels of noise. In the new algorithm, a linear modulated double-well potential is introduced to correct for the distortion of the output peak. Method parameter selection is convenient and intuitive for linear modulation. In order to achieve a better signal-to-noise ratio for the output signal, the performance of two-layer stochastic resonance was evaluated by comparing it with wavelet-based stochastic resonance. The proposed algorithm was applied to the quantitative analysis of dimethyl sulfide and the determination of chloramphenicol residues in milk, and the good linearity of the method demonstrated that it is an effective tool for detecting weak chromatographic peaks. Figure The linear modulation-based stochastic resonance algorithm (LSRA) improved the output chromatographic peak of chloramphenicol     

31P NMR study on the autophosphorylation of insulin receptors in the plasma membrane

A nonradioactive ³¹P nuclear magnetic resonance (NMR) spectroscopy protocol has been developed and used to investigate in vitro autophosphorylation of insulin receptors. Optimum experimental conditions have been explored, and the effects of Mn²⁺ and phosphocreatine (PCr) on the determination of the phosphorylation reaction have been assayed. The method was used to monitor the time courses of the phosphorylation reaction in solution. The results from this NMR study were in agreement with observations of insulin receptor phosphorylation made by using Western blotting.      

Application of anodized aluminum in fluorescence detection of biological species

Thin nanoporous alumina obtained by anodization of aluminum films offers promising advantages for application in fluorescence-based biological sensors including convenient preparation, increased density of binding sites, and improved collection efficiency of fluorescence. These advantages are illustrated in the detection of streptavidin using biotin covalently bound to the surface of alumina nanopores. Fluorescence intensity enhancement as high as 7 times is observed in nanopores in comparison to flat glass surface.      

Impedimetric genosensors for the detection of DNA hybridization

Impedance spectroscopy is proposed as the transduction principle for detecting the hybridization of DNA complementary strands. In our experiments, different DNA oligonucleotides were used as model gene substances. The gene probe is first immobilized on a graphite-epoxy composite working electrode based genosensor. Detection principle is based on changes of impedance spectra of a redox marker, the ferro/ferricyanide couple, after hybridization with target DNA. Resistance offered to the electrochemical reaction serves as the working signal, allowing for an unlabelled gene assay.      

Colorimetric detection of immunoglobulin G by use of functionalized gold nanoparticles on polyethylenimine film

A method based on use of functionalized gold nanoparticles on polyethylenimine film has been developed for colorimetric detection of immunoglobulin G (IgG). The immunogold nanoparticles were immobilized on quartz slides by recognition between antibody and antigen, with the antigen chemically adsorbed on the polyethylenimine film. By measurement of the UV–visible spectra of the immobilized immunogold, detection of h-IgG was achieved. The detection limit for h-IgG by use of this method can be as low as 0.01 μg mL⁻¹. This method is quite promising for numerous applications in immunoassay. Figure     

Recent advances in capillary electrophoretic analysis of individual cells

Because variability exists within populations of cells, single-cell analysis has become increasingly important for probing complex cellular environments. Capillary electrophoresis (CE) is an excellent technique for identifying and quantifying the contents of single cells owing to its small volume requirements and fast, efficient separations with highly sensitive detection. Recent progress in both whole-cell and subcellular sampling has allowed researchers to study cellular function in the areas of neuroscience, oncology, enzymology, immunology, and gene expression.      

Determination of trace elements in suspensions and filtrates of drinking and surface water by wavelength-dispersive X-ray fluorescence spectrometry

An X-ray fluorescence method (XRF) is presented that allowed low detection limits (at the 0.1–23 ng mL⁻¹ level) to be obtained for Cr, Mn, Fe, Ni, Zn, Sr, Pb, Bi and Br in water. The samples were prepared using a thin layer method. Trace elements were determined via the calibration curve and standard addition. Absorption effects and inhomogenities in prepared samples were checked for using the emission–transmission method and internal standards, respectively. The results from the XRF method were compared with the results from the inductively coupled plasma atomic emission spectrometry method.      

Study of the dynamics of surface molecules by time-resolved sum-frequency generation spectroscopy

Sum-frequency generation (SFG) is a nonlinear laser-spectroscopy technique suitable for analysis of adsorbed molecules. The sub-monolayer sensitivity of SFG spectroscopy enables vibrational spectra to be obtained with high specificity for a variety of molecules on a range of surfaces, including metals, oxides, and semiconductors. The use of ultra-short laser pulses on time-scales of picoseconds also makes time-resolved measurements possible; this can reveal ultrafast transient changes in molecular arrangements. This article reviews recent time-resolved SFG spectroscopy studies revealing site-hopping of adsorbed CO on metal surfaces and the dynamics of energy relaxation at water/metal interfaces. Time-resolved sum frequency generation spectroscopy at surfaces with non-resonant laser pulse irradiation     

Bienzyme sensors based on novel polymethylferrocenyl dendrimers

Amperometric bienzyme electrodes with horseradish peroxidase (HRP) and glucose oxidase (GOx) co-immobilized on polymethylferrocenyl dendrimers deposited onto platinum electrodes have been used for determination of the hydrogen peroxide produced by the oxidase during the enzymatic reaction. The redox dendrimers consist of flexible poly(propylenimine) dendrimer cores functionalised with octamethylferrocenyl units. The effects of dendrimer generation, the thickness of the dendrimer layer, substrate concentration, interferences, and reproducibility on the response of the sensors were investigated. The new bienzyme biosensors respond to substrate at work potential values between 200 and 50 mV (vs. SCE), have good sensitivity, and are resistant to interferences. Figure     

Determination of antimicrobial residues and metabolites in the aquatic environment by liquid chromatography tandem mass spectrometry

Antimicrobials are used in large quantities in human and veterinary medicine. Their environmental occurrence is of particular concern due to the potential spread and maintenance of bacterial resistance. After intake by the organisms, the unchanged drug and its metabolized forms are excreted and enter wastewater treatment plants where they are mostly incompletely eliminated, and are therefore eventually released into the aquatic environment. The reliable detection of several antimicrobials in different environmental aqueous compartments is the result of great improvements achieved in analytical chemistry. This article provides an overview of the more outstanding analytical methods based on liquid chromatography tandem mass spectrometry, developed and applied to determine antimicrobial residues and metabolites present in surface, waste, and ground waters.      

Comparison of three strategies to evaluate uncertainty from in-house validation data. A case study: mercury determination in sediments

In the present paper, three approaches are compared for the evaluation of the combined uncertainty in the determination of mercury in aquatic sediments by an aqua regia extraction procedure. For this, the data obtained in validation studies from five certified reference materials (CRMs), covering a range of concentrations from 0.8 to 130 mg kg⁻¹ of mercury and analysed by three atomic spectroscopic techniques (cold vapour generation atomic fluorescence spectrometry, CV-AFS, cold vapour generation atomic absorption spectroscopy, and inductively coupled plasma mass spectroscopy), were considered. The combined uncertainty was firstly assessed by considering separately the data obtained for each CRM analysed (approach A). Moreover, this assessment was also performed with two other calculation approaches (B and C) based on the pooled data obtained from the validation step. The comparison of the results obtained for the different techniques showed a clear bias effect when using CV-AFS with nitric acid as a diluent. In relation to the strategies tested for the combined uncertainty assessment, approach C proved to be the easiest and friendliest method for uncertainty assessment.      

Noninvasive methods for the investigation of ancient Chinese jades: an integrated analytical approach

This paper reports on an integrated analytical approach for the noninvasive characterization of Chinese nephrite samples, encompassing both geological reference specimens and museum objects. Natural variations induced by cationic substitutions, as well as human-induced alterations such as heating, which both affect color, are the focus of this contribution. Totally noninvasive methods of analysis were used, including X-ray fluorescence spectroscopy, Raman microspectroscopy, visible reflectance spectroscopy and X-ray diffraction; moreover, the feasibility of using a portable Raman spectrometer for the in-field identification of jades has been demonstrated. Fe/Fe+Mg (% p.f.u.) ratios of the jades have been calculated based on hydroxyl stretching Raman bands, which will provide an important addition to similar data that are being collected at major museums in the Western and Eastern hemispheres.      

A sequential injection electronic tongue employing the transient response from potentiometric sensors for anion multidetermination

Intelligent and automatic systems based on arrays of non-specific-response chemical sensors were recently developed in our laboratory. For multidetermination applications, the normal choice is an array of potentiometric sensors to generate the signal, and an artificial neural network (ANN) correctly trained to obtain the calibration model. As a great amount of information is required for the proper modelling, we proposed its automated generation by using the sequential injection analysis (SIA) technique. First signals used were steady-state: the equilibrium signal after a step-change in concentration. We have now adapted our procedures to record the transient response corresponding to a sample step. The novelty in this approach is therefore the use of the dynamic components of the signal in order to better discriminate or differentiate a sample. In the developed electronic tongue systems, detection is carried out by using a sensor array formed by five potentiometric sensors based on PVC membranes. For the developed application we employed two different chloride-selective sensors, two nitrate-selective sensors and one generic response sensor. As the amount of raw data (fivefold recordings corresponding to the five sensors) is excessive for an ANN, some feature extraction step prior to the modelling was needed. In order to attain substantial data reduction and noise filtering, the data obtained were fitted with orthonormal Legendre polynomials. In this case, a third-degree Legendre polynomial was shown to be sufficient to fit the data. The coefficients of these polynomials were the input information fed into the ANN used to model the concentrations of the determined species (Cl⁻, and ). Best results were obtained by using a backpropagation neural network trained with the Bayesian regularisation algorithm; the net had a single hidden layer containing three neurons with the tansig transfer function. The results obtained from the time-dependent response were compared with those obtained from steady-state conditions, showing the former superior performance. Finally, the method was applied for determining anions in synthetic samples and real water samples, where a satisfactory comparison was also achieved.