Chemiluminescent determination of adenosine, inosine, and hypoxanthine/xanthine

A fully automatic method for analysis of adenosine, inosine, and hypoxanthine/xanthine which combines the specificity of enzymatic catalysis and sensitivity of chemiluminescence is presented. The hydrogen peroxide formed by sequential catabolism of purines to uric acid is detected by the oxidation of luminol in the presence of peroxidase. The method takes advantage of the fact that light output in the H2O2/luminol system is transient. By adopting a two-step procedure this feature enables selective determination of adenosine, inosine, and hypoxanthine/xanthine. In step 1 any purines lower in the catabolic sequence than the analyte under study are converted to uric acid. Light emission is allowed to decay to baseline levels. During step 2 the analyte is selectively degraded. The H2O2 formed leads to a new light emission which is proportional to the square of analyte concentration. The method can be performed with commercially available reagents and enzymes and requires minimal processing of biological samples. Excellent agreement has been obtained with HPLC analysis. Sensitivity is in the range of 5-10 nmol/liter in as little as 0.1 ml. More than 200 samples per day can be analyzed by a single operator.     

Comparative measurements of multicomponent phospholipid mixtures by electrospray mass spectroscopy: relating ion intensity to concentration

Electrospray mass spectrometry allows direct identification and sensitive detection of multiple phospholipids in non-derivatized cell extracts. However, quantitative analyses are not straightforward, and are confounded by analyte and mass discrimination effects, and non-linear dependence of the ion intensity on concentration. This non-linearity is particularly severe in the negative mode and precludes even comparative measurements of anion concentrations. Herein, we report a general method for relating negative electrospray ion intensity to concentration when analyzing multicomponent phospholipid samples. In this method, the intensity of individual ions is measured at several different concentrations of the total mixture and the slope (n(E)) of the double log plot of sample concentration vs. intensity for each analyte is determined. The n(E) is then used to map intensity data to a quantity proportional to concentration for each analyte. The method allows facile and accurate comparison of negative spectra of complex mixtures containing structurally different anions.     

Evaluation of absolute peptide quantitation strategies using selected reaction monitoring

The use of internal peptide standards in selected reaction monitoring experiments enables absolute quantitation. Here, we describe three approaches addressing calibration of peptide concentrations in complex matrices and assess their performance in terms of trueness and precision. The simplest approach described is single reference point quantitation where a heavy peptide is spiked into test samples and the endogenous analyte quantified relative to the heavy peptide internal standard. We refer to the second approach as normal curve quantitation. Here, a constant amount of heavy peptide and a varying amount of light peptide are spiked into matrix to construct a calibration curve. This accounts for matrix effects but due to the presence of endogenous analyte, it is usually not possible to determine the lower LOQ. We refer to the third method as reverse curve quantitation. Here, a constant amount of light peptide and a varying amount of heavy peptide are spiked into matrix to construct a calibration curve. Because there is no contribution to the heavy peptide signal from endogenous analyte, it is possible to measure the equivalent of a blank sample and determine LOQ. These approaches are applied to human plasma samples and used to assay peptides of a set of apolipoproteins.     

Methodology for real-time,multianalyte monitoring of fermentations using an in-situ mid-infrared sensor

An in-situ, mid-infrared sensor was used to monitor the major analyte concentrations involved in the cultivation of Gluconacetobacter xylinus and the production of gluconacetan, a food-grade exopolysaccharide. To predict the analyte concentrations, three different sets of standard spectra were used to develop calibration models, applying partial least-squares regression. It was possible to build a valid calibration model to predict the 700 spectra collected during the complete time course of the cultivation, using only 12 spectra collected every 10 h as standards. This model was used to reprocess the concentration profiles from 0 to 15 g/L of nine different analytes with a mean standard error of validation of 0.23 g/L. However, this calibration model was not suitable for real-time monitoring as it was probably based on non-specific spectral features, which were correlated only with the measured analyte concentrations. Valid calibration models capable of real-time monitoring could be established by supplementing the set of 12 fermentation spectra with 42 standards of measured analytes. A pulse of 5 g/L ethanol showed the robustness of the model to sudden disturbances. The prediction of the models drifted, however, toward the end of the fermentation. The most robust calibration model was finally obtained by the addition of 34 standard spectra of non-measured analytes. Although the spectra did not contain analyte-specific information, it was believed that this addition would increase the variability space of the calibration model. Therefore, an expanded calibration model containing 88 spectra was used to monitor, in real time, the concentration profiles of fructose, acetic acid, ethanol and gluconacetan and allowed standard errors of prediction of 1.11, 0.37, 0.22, and 0.79 g/L, respectively.     

A hybrid least squares and principal component analysis algorithm for Raman spectroscopy

Raman spectroscopy is a powerful technique for detecting and quantifying analytes in chemical mixtures. A critical part of Raman spectroscopy is the use of a computer algorithm to analyze the measured Raman spectra. The most commonly used algorithm is the classical least squares method, which is popular due to its speed and ease of implementation. However, it is sensitive to inaccuracies or variations in the reference spectra of the analytes (compounds of interest) and the background. Many algorithms, primarily multivariate calibration methods, have been proposed that increase robustness to such variations. In this study, we propose a novel method that improves robustness even further by explicitly modeling variations in both the background and analyte signals. More specifically, it extends the classical least squares model by allowing the declared reference spectra to vary in accordance with the principal components obtained from training sets of spectra measured in prior characterization experiments. The amount of variation allowed is constrained by the eigenvalues of this principal component analysis. We compare the novel algorithm to the least squares method with a low-order polynomial residual model, as well as a state-of-the-art hybrid linear analysis method. The latter is a multivariate calibration method designed specifically to improve robustness to background variability in cases where training spectra of the background, as well as the mean spectrum of the analyte, are available. We demonstrate the novel algorithm's superior performance by comparing quantitative error metrics generated by each method. The experiments consider both simulated data and experimental data acquired from in vitro solutions of Raman-enhanced gold-silica nanoparticles.     

Quantification of endogenous steroids in human urine by gas chromatography mass spectrometry using a surrogate analyte approach

Providing “real blank sample” is a problem in determination of endogenous steroids in complex matrices. A new quantification strategy is proposed in the present study, which is based on using isotope-labeled steroids instead of natural steroids for constructing calibration line. This approach is called surrogate analyte and it is shown that its accuracy is better than some of the previously described methods at low concentrations and comparable to standard addition method at medium and high concentration levels. The method was fully validated to satisfy the ICH criteria and it was applied for determination of endogenous steroids in several urine samples.     

Analyte and internal standard cross signal contributions and their impact on quantitation in LC-MS based bioanalysis

Cross signal contributions between an analyte and its internal standard (IS) are very common due to impurities in reference standards and/or isotopic interferences. Despite the general awareness of this issue, how exactly they affect quantitation in LC-MS based bioanalysis has not been systematically evaluated. In this research, such evaluations were performed first by simulations and then by experiments using a typical bioanalytical method for tiagabine over the concentration range of 1-1000 ng/mL in human EDTA K(3) plasma. The results demonstrate that when an analyte contributes to IS signal, linearity and accuracy can be affected with low IS concentration. Thus, minimum IS concentrations have been obtained for different combinations of concentration range, percentage of cross contribution, and weighting factor. Moreover, while impurity in analyte reference standard is a factor in cross signal contribution, significant systematic errors could exist in the results of unknown samples even though the results of calibration standards and quality controls are acceptable. How these systematic errors would affect stability evaluation, method transfer, and cross validation has also been discussed and measures to reduce their impact are proposed. On the other hand, the signal contribution from an IS to the analyte causes shifting of a calibration curve, i.e. increase of intercept, and theoretically, the accuracy is not affected. The simulation results are well supported by experimental results. For example, good inter-run (between-run) accuracy (bias: -2.70 to 5.35%) and precision (CV: 2.07-10.50%) were obtained when runs were extracted with an IS solution containing 1-fold of the lower limit of quantitation.     

In situ quantification of microcarrier animal cell cultures using near-infrared spectroscopy

In-line monitoring tools are still required to understand and control animal cell processes, particularly in the case of vaccine production. Here, in situ near-infrared spectroscopy (NIRS) quantification of components in culture media was performed using microcarrier-based cultivations of adherent Vero cells. Because microcarriers were found to interfere with NIRS spectra acquisition, a suitable and innovative in situ calibration was developed for bioreactor cultures. A reliable and accurate NIRS technique for the quantification of glucose and lactate was established, with a calibration standard error of 0.30 and 0.21 g l⁻¹, respectively. The robustness of this method was evaluated by performing NIRS calibration with operating conditions similar to those of industrial processes, including parameters such as microcarrier concentrations, cell seeding states and changes in analyte concentration due to feed and harvest strategies. Based on this calibration procedure, the predicted analyte concentrations in unknown samples was measured by NIRS analyses with an accuracy of 0.36 g l⁻¹ for glucose and 0.29 g l⁻¹ for lactate.     

In situ quantification of microcarrier animal cell cultures using near-infrared spectroscopy

In-line monitoring tools are still required to understand and control animal cell processes, particularly in the case of vaccine production. Here, in situ near-infrared spectroscopy (NIRS) quantification of components in culture media was performed using microcarrier-based cultivations of adherent Vero cells. Because microcarriers were found to interfere with NIRS spectra acquisition, a suitable and innovative in situ calibration was developed for bioreactor cultures. A reliable and accurate NIRS technique for the quantification of glucose and lactate was established, with a calibration standard error of 0.30 and 0.21 g l⁻¹, respectively. The robustness of this method was evaluated by performing NIRS calibration with operating conditions similar to those of industrial processes, including parameters such as microcarrier concentrations, cell seeding states and changes in analyte concentration due to feed and harvest strategies. Based on this calibration procedure, the predicted analyte concentrations in unknown samples was measured by NIRS analyses with an accuracy of 0.36 g l⁻¹ for glucose and 0.29 g l⁻¹ for lactate.     

Nondestructive near-infrared spectroscopic measurement of multiple analytes in undiluted samples of serum-based cell culture media.

An adaptive calibration procedure is used to build selective multivariate calibration models for the measurement of glucose, lactate, glutamine, and ammonia in undiluted serum-based cell culture media. This adaptive procedure removes metabolism-induced covariance between these analytes in a series of calibration samples collected during the cultivation of PC-3 human prostate cancer cells. Partial least-squares calibration models are generated from single-beam near-infrared (NIR) spectra collected over the 4800- to 4200-cm(-1) combination spectral range. Calibration models were generated with both the full spectral range and optimized spectral ranges. In both cases, the number of model factors was optimized and model validity was determined by comparing analyte concentrations predicted from a series of independent and unaltered samples that were obtained during a subsequent cultivation of the PC-3 cells. Similar analytical performance was achieved with fewer model factors when the optimized spectral range was used. The lowest standard errors of prediction were 0.82, 0.94, 0.55, and 0.76 mM for glucose, lactate, glutamine, and ammonia, respectively. Different spectral ranges were optimal for each analyte and the optimized spectral range coincided with the distinguishing spectral features of the analyte. The results of this study demonstrate that NIR spectroscopy can be used effectively in the off-line measurement of important nutrients (glucose and glutamine) and byproducts (lactate and ammonia) in a serum-based animal cell culture medium.     

Simultaneous determination of JTT-501 and its main metabolite in human plasma by liquid chromatography-ionspray mass spectrometry

An LC-MS-MS analytical method was developed for the determination of a new antidiabetic agent, JTT-501 and its main metabolite (JTP-20604) in human plasma. The compounds were isolated from plasma by protein precipitation before analysis by HPLC with atmospheric pressure positive ionisation MS-MS detection. An isotopically labelled analog of JTT-501 was used as the internal standard. Linearity was demonstrated over the calibration range of about 5-10000 ng/ml for both compounds. The assay was validated with respect to accuracy, precision and analyte stability. This method was used for the determination of plasma concentrations for the two compounds in a clinical tolerability study. A cross-validation exercise between two different mass spectrometers, used for the determination of clinical samples, is also reported.     

Direct chemiluminescence determination of ibuprofen by the enhancement of the KMnO(4)-sulphite reaction.

A simple, rapid, flow-injection chemiluminescence (CL) method is described for the determination of ibuprofen. A strong CL signal was detected when a mixture of the analyte and sulphite was injected into acidic KMnO(4). The CL signal is proportional to the concentration of ibuprofen in the range 0.1-10.0 mg/L. The detection limit is 0.02 mg/L ibuprofen, the relative standard deviation is 1.8% (0.5 mg/L ibuprofen; n = 11) and the sample measurement frequency is 120/h. The proposed method was successfully applied to the determination of ibuprofen in pharmaceutical preparations and in spiked urine samples. The mechanism of the CL reaction is also discussed.     

Simultaneous direct determination of amiloride and triamterene in urine using isopotential fluorometry

A method for the simultaneous fluorometric determination of two diuretics in urine is proposed. The combination of matrix isopotential synchronous fluorescence (MISF) and first derivative techniques provides good analytical results. MISF spectra are obtained by calculating the isopotential trajectory in the three-dimensional fluorescence spectrum for a urine solution. In the spectral contour, the trajectory is taken to be the portion of the line that passes by the fluorescence maxima of both diuretics (lambda(ex) = 365 and lambda(em) = 413 nm for amiloride and lambda(ex) = 365 and lambda(em) = 437 nm for triamterene). Because contour lines connect points of identical intensity and the trajectory is part of a contour line, it is called "isopotential." Analyses was carried out in a 1/1 (v/v) ethanol/water mixture, using an apparent pH of 6.3 provided by 0.01 M sodium/citrate citric acid buffer. Urine samples are diluted 50 times and provide linear calibration plots at amiloride and triamterene concentrations up to 320 and 100 ng mL(-1), respectively. The goodness of the analytical signal was checked by using variance analysis. Signals recorded throughout the calibration range were subjected to three calibrations per each analyte, both in the absence and in the presence of variable amounts of the other analyte. Differences between individual calibrations and slopes were compared with those within individual calibrations. Based on the results, triamterene and amiloride can be accurately quantified in the presence of each other. The limit of detection calculated according to Clayton who uses error propagation throughout the calibration curve and a noncentralized security factor was 16.8 and 2.4 ng mL(-1) for amiloride and triamterene, respectively.     

Spectral surface plasmon resonance imaging for the detection of clenbuterol via three-dimensional immobilization of bioprobes

A method of immobilizing clenbuterol (CLEN) on the sensor chip for spectral surface plasmon resonance imaging (SPRi) was experimentally investigated. The bioprobes on the sensor chip were prepared by immobilizing bovine serum albumin (BSA) protein and conjugating CLEN molecules to BSA, which provides more active points and free orientations for specific binding. The calibration curve showed that the wavelength resonance shift decreased as the concentration of CLEN analyte increased, consistent with the inhibition principle. The limit of detection (LOD) was estimated to be 6.32 μg/ml. This method proved to be highly specific, high throughput, label free, and operationally convenient.     

Bayesian Estimation of the Active Concentration and Affinity Constants Using Surface Plasmon Resonance Technology

Surface plasmon resonance (SPR) has previously been employed to measure the active concentration of analyte in addition to the kinetic rate constants in molecular binding reactions. Those approaches, however, have a few restrictions. In this work, a Bayesian approach is developed to determine both active concentration and affinity constants using SPR technology. With the appropriate prior probabilities on the parameters and a derived likelihood function, a Markov Chain Monte Carlo (MCMC) algorithm is applied to compute the posterior probability densities of both the active concentration and kinetic rate constants based on the collected SPR data. Compared with previous approaches, ours exploits information from the duration of the process in its entirety, including both association and dissociation phases, under partial mass transport conditions; do not depend on calibration data; multiple injections of analyte at varying flow rates are not necessary. Finally the method is validated by analyzing both simulated and experimental datasets. A software package implementing our approach is developed with a user-friendly interface and made freely available.     

Application of the standard addition approach for the quantification of urinary benzene

Urinary benzene is used as biomarker of exposure to evaluate the uptake of this solvent both in non-occupationally exposed population and in benzene-exposed workers. The quantitative determination of benzene in urine is carried out in a three steps procedure: urine collection, sample analysis by head space/solid phase microextraction/gas chromatography/mass spectrometry and analyte quantification. The adopted quantification method influences the initial step, hence the whole procedure. Two quantification approaches were compared as regards precision and accuracy: the calibration curves and the standard addition method. Even if calibration curves obtained by using urine samples from different subjects were always linear, their slopes and intercepts showed noteworthy variations, attributable to the influence of the biological matrix on benzene recovery. The standard addition method showed to be more suitable for compensating matrix effects, and a three-point standard addition protocol was used to quantify benzene in urine samples of 11 benzene-exposed workers (smokers and non-smokers). Urine from occupationally exposed workers was collected before and after work-shift. Besides urinary benzene, the applicability of the method was verified by measuring the urinary concentration of the S-phenylmercapturic acid, a specific benzene metabolite, generally adopted as biomarker in biological monitoring procedures. A similar trend of concentration levels of both analytes measured in urine samples collected before work-shift with respect to the after work-shift ones was found, showing the actual applicability of the standard addition method for biological monitoring purposes.     

Multiwavelength method for measuring concentration of free cytosolic calcium using the fluorescent probe indo-1

It is assumed that the spectra of fluorescent probes indo-1 and fura-2 in the cytoplasm are linear combinations of the spectra of calcium-bound and free probes with weight factors proportional to the concentrations of these forms. When the concentration of calcium is measured by the dual-wavelength method, the above assumption is employed without testing. A multiwavelength method for measuring free cytosolic calcium concentration is described in the present study. The method is based on the registration of the fluorescence spectra of the probe with an optical multichannel analyzer and deconvolution of the spectra into components, corresponding to free and bound forms of the probe. A mismatch is also calculated to allow estimation of deconvolution accuracy. It was found that the spectra, recorded in aqueous calibration solution with varying calcium concentrations, can be deconvoluted into components, obtained both in the absence of calcium and at its saturating concentration. When the spectrum of the probe in the cytoplasm is deconvoluted into the same components the mismatch is higher. When aqueous calibration is used, the cytosolic calcium concentration determined by the dual-wavelength method is dependent considerably on the selected wavelengths. Our data indicate that this phenomenon may be associated with the lower polarity of cytoplasm compared to the aqueous calibration solution. Addition of either ethanol or glycerol into the calibration medium results in a considerable decrease in the mismatch. The optimal concentration of ethanol is 22-32%, and depends on the type and condition of cells tested. It is shown that the use of calibration spectra obtained in aqueous solutions leads to considerable overestimation of cytosolic calcium concentration.     

Microemulsion electrokinetic chromatography for the separation of arctiin and arctigenin in Fructus Arctii and its herbal preparations

A microemulsion electrokinetic chromatography method was used to separate arctiin and arctigenin in Fructus Arctii and its herbal preparations. The separation of arctiin and arctigenin was performed using a 1-butanol-SDS-ethyl acetate-water microemulsion in 10mM sodium tetraborate buffer. The analytes were baseline-resolved within 4 min. In the concentration range 5-500 microg/mL, the calibration curves reveal linear relationships between the peak area for each analyte and its concentration (correlation coefficients: 0.9993 for arctiin and 0.9998 for arctigenin). The method was applied to the analysis of arctiin and arctigenin in herbal preparations, and the recoveries were 98.7-103.1% for arctiin and 97.6-103.2% for arctigenin, respectively.     

Rapid and sensitive detection of microcystin by immunosensor based on nuclear magnetic resonance

A stable and sensitive toxin residues immunosensor based on the relaxation of magnetic nanoparticles was developed. The method was performed in one reaction and offered sensitive, fast detection of target toxin residues in water. The target analyte, microcystin-LR (MC-LR) in Tai lake water, competed with the antigens on the surface of the magnetic nanoparticles and then influenced the formation of aggregates of the magnetic nanoparticles. Accordingly, the magnetic relaxation time of the magnetic nanoparticles was changed under the effect of the target analyte. The calibration curve was deduced at different concentrations of the target analyte. The limit of detection (LOD) of MC-LR was 0.6 ng g⁻¹ and the detection range was 1–18 ng g⁻¹. Another important feature of the developed method was the easy operation: only two steps were needed (1) to mix the magnetic nanoparticle solution with the sample solution and (2) read the results through the instrument. Therefore, the developed method may be a useful tool for toxin residues sensing and may find widespread applications.     

A simple method for bracketing absolute divergence times on molecular phylogenies using multiple fossil calibration points

A central challenge facing the temporal calibration of molecular phylogenies is finding a quantitative method for estimating maximum age constraints on lineage divergence times. Here, I provide such a method. This method requires an ultrametric tree generated without reference to the fossil record. Exploiting the fact that the relative branch lengths on the ultrametric tree are proportional to time, this method identifies the lineage with the greatest proportion of its true temporal range covered by the fossil record. The oldest fossil of this calibration lineage is used as the minimum age constraint. The maximum age constraint is obtained by adding a confidence interval onto the end point of the calibration lineage, thus making it possible to bracket the true divergence times of all lineages on the tree. The approach can also identify fossils that have been grossly misdated or misassigned to the phylogeny. The method assumes that the relative branch lengths on the ultrametric tree are accurate and that fossilization is random. The effect of violations of these assumptions is assessed. This method is simple to use and is illustrated with a reanalysis of Near et al.'s turtle data.