Measurement of Caffeine Metabolites in Urine Using Diode-Array Detection HPLC

Abstract

Diode-array detection high performance liquid chromatography (HPLC) offers significant advantages when compared to conventional UV HPLC detection. These advantages include important spectral information such as the τ max and the UV spectra of each eluting peak. The spectral scans are obtained at the peak start, peak apex and peak end. This provides a comparison of these spectra so that peak homogeneity can be calculated. Standard spectra can be stored and compared to eluting peaks for “purity”. Therefore, peak identification is based not only on retention time but the aforementioned spectral information.

Recently, pathways involved in the metabolism of caffeine have been determined. One of the pathways involves the N-acetyltransferase system. Thus, a safe non-invasive and convenient procedure is now available to determine the N-acetylation phenotype. This is important because a number of toxicities have been associated with acetylator phenotype.

The present paper indicates the utility of the diode-array detector for performing these studies. Use of this detector provides greater accuracy and reliability in correctly identifying the key metabolites required for classification as compared to conventional detection HPLC.     

Calculation and optimization of sample identification by laser induced breakdown spectroscopy via correlation analysis

Linear correlation analysis may be used as a technique for the identification of samples with a very similar chemical composition by laser induced breakdown spectroscopy. The spectrum of the “unknown” sample is correlated with a library of reference spectra. The probability of identification by single shot analysis can be estimated by the method described in this paper. When a right identification is not obtained by single shot correlation analysis the accuracy can be increased by averaging spectra or by averaging the correlation coefficients. The number of spectra or correlation coefficients to be averaged to obtain a 99.9% right identification is evaluated. We found out that the number of spectra to be averaged is equal to the number of correlation coefficients to be averaged. The benefit of using averaged spectra over averaging correlation coefficients is a faster calculation.     

Spectral unmixing and clustering algorithms for assessment of single cells by Raman microscopic imaging

A detailed comparison of six multivariate algorithms is presented to analyze and generate Raman microscopic images that consist of a large number of individual spectra. This includes the segmentation algorithms for hierarchical cluster analysis, fuzzy C-means cluster analysis, and k-means cluster analysis and the spectral unmixing techniques for principal component analysis and vertex component analysis (VCA). All algorithms are reviewed and compared. Furthermore, comparisons are made to the new approach N-FINDR. In contrast to the related VCA approach, the used implementation of N-FINDR searches for the original input spectrum from the non-dimension reduced input matrix and sets it as the endmember signature. The algorithms were applied to hyperspectral data from a Raman image of a single cell. This data set was acquired by collecting individual spectra in a raster pattern using a 0.5-??m step size via a commercial Raman microspectrometer. The results were also compared with a fluorescence staining of the cell including its mitochondrial distribution. The ability of each algorithm to extract chemical and spatial information of subcellular components in the cell is discussed together with advantages and disadvantages.     

Denoising of gamma-ray spectrum by optimized wavelet thresholding based on modified genetic algorithm in carbon/oxygen logging

In order to reduce noise in gamma-ray spectrum measured by carbon/oxygen logging instrument, an improved wavelet thresholding algorithm was proposed in this paper. This algorithm established a thresholding function with an adjustable parameter, which could obtain various filtering performances by means of different parameters, and then a modified genetic algorithm combined with opposition-based learning theory was put forward to optimize the parameter and wavelet thresholds. By using Monte Carlo simulation, the objective function of the modified genetic algorithm was determined. Finally, the actual measured spectra processing results of the optimized wavelet thresholding algorithm was compared with traditional thresholding algorithms and other filtering algorithms, and the effectiveness of the proposed algorithm was verified based on signal-to-noise ratio index.

     

Fluorescence Analysis: A New Approach

Abstract

The Video Fluorometer is a new instrument for fluorescence analysis which offers significant advantages for the study of complex systems. This instrument can acquire 241 fluorescence spectra, taken at 241 different exciting wavelengths in 16.7 milliseconds. These results are displayed in a three-dimensional graphical format in real time. Coupled with a laboratory computer, this instrument should provide new algorithms for the analysis of luminescence spectra of multi-component systems.     

Genetic algorithms (GA) applied to the orthogonal projection approach (OPA) for variable selection

Multivariate curve resolution (MCR) and especially the orthogonal projection approach (OPA) can be applied to spectroscopic data and were proved to be suitable for process monitoring. To improve the quality of the on-line monitoring of batch processes, it is interesting to get as many as possible spectra in a given period of time. Nevertheless, hardware limitations could lead to the fact that it is not possible to acquire more than a certain number of spectra in this given period of time. Wavelength selection could be a good way to limit this problem since it decreases size, and consequently the acquisition time, of each recorded spectrum. This paper details an industrial application of genetic algorithms (GA) coupled with a curve resolution method (OPA) for such purpose.     

Post-acquisition ETD spectral processing for increased peptide identifications

Tandem mass spectra (MS/MS) produced using electron transfer dissociation (ETD) differ from those derived from collision-activated dissociation (CAD) in several important ways. Foremost, the predominant fragment ion series are different: c- and z ^·-type ions are favored in ETD spectra while b- and y-type ions comprise the bulk of the fragments in CAD spectra. Additionally, ETD spectra possess charge-reduced precursors and unique neutral losses. Most database search algorithms were designed to analyze CAD spectra, and have only recently been adapted to accommodate c- and z ^·-type ions; therefore, inclusion of these additional spectral features can hinder identification, leading to lower confidence scores and decreased sensitivity. Because of this, it is important to pre-process spectral data before submission to a database search to remove those features that cause complications. Here, we demonstrate the effects of removing these features on the number of unique peptide identifications at a 1% false discovery rate (FDR) using the open mass spectrometry search algorithm (OMSSA). When analyzing two biologic replicates of a yeast protein extract in three total analyses, the number of unique identifications with a ∼1% FDR increased from 4611 to 5931 upon spectral pre-processing—an increase of ∼28. 6%. We outline the most effective pre-processing methods, and provide free software containing these algorithms.     

Detection of illicit substances in fingerprints by infrared spectral imaging

FTIR and Raman spectral imaging can be used to simultaneously image a latent fingerprint and detect exogenous substances deposited within it. These substances might include drugs of abuse or traces of explosives or gunshot residue. In this work, spectral searching algorithms were tested for their efficacy in finding targeted substances deposited within fingerprints. “Reverse” library searching, where a large number of possibly poor-quality spectra from a spectral image are searched against a small number of high-quality reference spectra, poses problems for common search algorithms as they are usually implemented. Out of a range of algorithms which included conventional Euclidean distance searching, the spectral angle mapper (SAM) and correlation algorithms gave the best results when used with second-derivative image and reference spectra. All methods tested gave poorer performances with first derivative and undifferentiated spectra. In a search against a caffeine reference, the SAM and correlation methods were able to correctly rank a set of 40 confirmed but poor-quality caffeine spectra at the top of a dataset which also contained 4,096 spectra from an image of an uncontaminated latent fingerprint. These methods also successfully and individually detected aspirin, diazepam and caffeine that had been deposited together in another fingerprint, and they did not indicate any of these substances as a match in a search for another substance which was known not to be present. The SAM was used to successfully locate explosive components in fingerprints deposited on silicon windows. The potential of other spectral searching algorithms used in the field of remote sensing is considered, and the applicability of the methods tested in this work to other modes of spectral imaging is discussed.     

Design-of-experiment optimization of exhaled breath condensate analysis using a miniature differential mobility spectrometer (DMS)

Analytical instruments that can measure small amounts of chemicals in complicated biological samples are often useful as diagnostic tools. However, it can be challenging to optimize these sensors using actual clinical samples, given the heterogeneous background and composition of the test materials. Here we use gas chromatography-differential mobility spectrometry (GC/DMS) to analyze the chemical content of human exhaled breath condensate (EBC). Ultimately, this system can be used for non-invasive disease diagnostics. Many parameters can be adjusted within this instrument system, and we implemented a factorial design-of-experiments to systematically test several combinations of parameter settings while concurrently analyzing effects and interactions.We examined four parameters that affect sensitivity and detection for our instrument, requiring a 2⁴ factorial design. We optimized sensor function using EBC samples spiked with acetone, a known clinical biomarker in breath. Two outputs were recorded for each experiment combination: number of chemicals detected, and the amplitude of acetone signal. Our goal is to find the best parameter combination that yields the highest acetone peak while also preserving the largest number of other chemical peaks in the spectra. By optimizing the system, we can conduct further clinical experiments with our sensor more efficiently and accurately.     

An economical two-step method with optimal phase and stability properties for problems in chemistry

A new ECONO2STEP (economical two-step) method with eliminated phase-lag and its derivatives up to order six is developed in this paper. The newly developed method can be applied to initial or boundary value problems with oscillating and/or periodical solutions. We applied the new method to problems in Quantum Chemistry. The newly introduced method is called economical since using the minimum number of function evaluations per step achieves the highest possible algebraic order.

     

Computer-assisted interpretation of atmospheric pressure chemical ionization mass spectra of triacylglycerols

Current lipidomics approaches require simple and rapid algorithms enabling the interpretation of mass spectra of lipids. Most lipids are complex mixtures of related components in which the composition of the aliphatic fatty acid chains varies from one molecule to the next. Triacylglycerols (TAGs) are an example of such a lipid class. Fatty acid chains are the only parts of the molecule to change from one species to another. Fatty acids, and consequently also TAGs, can be characterized by two parameters; the number of carbon atoms and the number of double bonds. All calculations reflecting relations among ions in the spectra can be easily made using these parameters. An algorithm for the automated interpretation of TAGs from atmospheric pressure chemical ionization mass spectra (TriglyAPCI) is presented in this paper. The algorithm first identifies diacylglycerol fragments and molecular adducts. In the next step, relations among the ions are searched and possible TAG structures are suggested. Individual features of the algorithm are described in detail and the software performance is demonstrated for the liquid chromatography/mass spectrometric (LC/MS) analysis of TAGs isolated from the termite Prorhinotermes canalifrons.     

Extraction of multiple pure component H and C NMR spectra from two mixtures: Novel solution obtained by sparse component analysis-based blind decomposition

Sparse component analysis (SCA) is demonstrated for blind extraction of three pure component spectra from only two measured mixed spectra in ¹³C and ¹H nuclear magnetic resonance (NMR) spectroscopy. This appears to be the first time to report such results and that is the first novelty of the paper. Presented concept is general and directly applicable to experimental scenarios that possibly would require use of more than two mixtures. However, it is important to emphasize that number of required mixtures is always less than number of components present in these mixtures. The second novelty is formulation of blind NMR spectra decomposition exploiting sparseness of the pure components in the wavelet basis defined by either Morlet or Mexican hat wavelet. This enabled accurate estimation of the concentration matrix and number of pure components by means of data clustering algorithm and pure components spectra by means of linear programming with constraints from both ¹H and ¹³C NMR experimental data. The third novelty is capability of proposed method to estimate number of pure components in demanding underdetermined blind source separation (uBSS) scenario. This is in contrast to majority of the BSS algorithms that assume this information to be known in advance. Presented results are important for the NMR spectroscopy-associated data analysis in pharmaceutical industry, medicine diagnostics and natural products research.     

Proof of principle of a generalized fuzzy Hough transform approach to peak alignment of one-dimensional <Superscript>1</Superscript>H NMR data

In metabolic profiling, multivariate data analysis techniques are used to interpret one-dimensional (1D) ¹H NMR data. Multivariate data analysis techniques require that peaks are characterised by the same variables in every spectrum. This location constraint is essential for correct comparison of the intensities of several NMR spectra. However, variations in physicochemical factors can cause the locations of the peaks to shift. The location prerequisite may thus not be met, and so, to solve this problem, alignment methods have been developed. However, current state-of-the-art algorithms for data alignment cannot resolve the inherent problems encountered when analysing NMR data of biological origin, because they are unable to align peaks when the spatial order of the peaks changes—a commonly occurring phenomenon. In this paper a new algorithm is proposed, based on the Hough transform operating on an image representation of the NMR dataset that is capable of correctly aligning peaks when existing methods fail. The proposed algorithm was compared with current state-of-the-art algorithms operating on a selected plasma dataset to demonstrate its potential. A urine dataset was also processed using the algorithm as a further demonstration. The method is capable of successfully aligning the plasma data but further development is needed to address more challenging applications, for example urine data. Figure Traces of NMR peaks visualizing the Generalized Fuzzy Hough Transform (GFHT) method for elucidating peak correspondence between samples. The spectra are sorted according to one shift sensitive peak and reveals that other peaks exhibit a similar shift pattern. This pattern(s) can now be searched for using the GFHT. The red and black spectra in the figure are the most shifting spectra (top and bottom), by following the GFHT traces peak correspondence is easily established although peaks change spatial location Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Deconvolution of lignin fluorescence spectra: A contribution to the comparative structural studies of lignins

In this work, we deconvoluted the fluorescence spectra of lignin and a lignin model compound using a combination of one symmetric (Gaussian) and the most appropriate number of asymmetric (Log-normal) models. We aimed to obtain new data on the structural characteristics of lignin as a complex molecule using fluorescence spectroscopy in combination with FTIR spectra. We analyzed the emission spectra of the lignin model compound, DHP, and isolated lignins from a deciduous tree, poplar, and a coniferous tree, spruce. The number of applied asymmetric components was varied for each sample until the component positions obtained from deconvolution of a series of spectra became constant. The lignin model compound contains fewer components in the emission spectrum. The same components in the spectra of all three samples show that they contain the same fluorophores. The small shift of the peak position can be attributed to the influence of different environments. The FTIR spectra of the three polymers show a small difference between their structures. The main difference among the IR spectra of the three samples is in the intensity of some peaks. The text was submitted by the authors in English.     

Determination of Lanthanide (III) Ions by Using a Flotation - Spectrophotometric Method

Abstract

This paper reports our attempt at determining Ln (III) ions by using a flotation-spectrophotometric method and our findings. When a ternary ion-association complex of Ln (III) coordinated by thiocyanate (SCN^?) and diantipyryl methane (DA[Mdot]) is separated by a mixed solvent containing benzene and chloroform at pH 3.1 – 4.2, a third phase is observed between the aqueous and organic phases. The solid ternary complex can be dissolved in acetone that contains thenoyltrifluoroacetone (TTA). The individual Ln (III) ion can be determined by using the 4th derivative spectra directly. The equilibrium constant of the ternary composition ratio of Ln(II1) to ligand is estimated by the equilibrium shift method. The mole ratio of Ln(II1) to DAM and to SCN^? is 1:3 each. The composition of the tcrnary complex seems to be Ln(III):DAM:SCN^?=1:3:3.     

A Simple Method of Evaluating Particle Size Distributions and Settling Rates for Silica Based Chromatographic Supports

Abstract

A simple and inexpensive method of evaluating particle settling rates and the particle size distribution of chromatographic supports using common laboratory equipment is reported. The time dependence of the turbidity of a solution of silica support particles suspended in an appropriate liquid is measured on a spectrometer. Digital acquisition allows data manipulation using simple algorithms to yield the distribution of particle sizes based on the Stoke's diameter. This data can easily be transformed into the most useful form for presentation, e.g. number average, weight average, cumulative distribution, etc.     

Territorial origin of olive oil: representing georeferenced maps of olive oils by NMR profiling

ABSTRACT Proton NMR profiling is nowadays a consolidated technique for the identification of geographical origin of food samples. The common approach consists in correlating NMR spectra of food samples to their territorial origin by multivariate classification statistical algorithms. In the present work, we illustrate an alternative perspective to exploit territorial information, contained in the NMR spectra, which is based on the implementation of a geographic information system (GIS). Nuclear magnetic resonance spectra are used to build a GIS map permitting the identification of territorial regions having strong similarities in the chemical content of the produced food (terroir units). These terroir units can, in turn, be used as input for labeling samples to be analyzed by traditional classification methods. In this work, we describe the methods and the algorithms that permit to produce GIS maps from NMR profiles and apply the described method to the analysis of the geographical distribution of olive oils in an Italian region. In particular, we analyzed by ¹H NMR up to 98 georeferenced olive oil samples produced in the Abruzzo Italian region. By using the first principal component of the NMR variables selected according to the Moran test, we produced a GIS map, in which we identified two regions incidentally corresponding to the provinces of Teramo and Pescara. We then labeled the samples according to the province of provenience and built an LDA model that provides a classification ability up to 99% . A comparison between the variables selected in the geostatistics and classification steps is finally performed. Copyright © 2016 John Wiley & Sons, Ltd.     

Search strategy and data compression for a retrieval system with binary-coded mass spectra

A retrieval system for binary-coded mass spectra is described. The data base used contains 9628 low-resolution mass spectra from the Aldermaston Mass Spectra Data Collection. These spectra are reduced to 106 preselected binary-coded m/z values each. Storage of the compound names and formulae is minimized by using a special set of characters and file organization. The search strategy permits fast generation of the N- nearest neighbours. Depending on the number of best matches generated, an average search requires access to only 24—33% of the spectra contained in the data base. Because of its limited storage requirements, this search system can be used even on microcomputers.l]     

Quantitative reproducibility of mass spectra in matrix‐assisted laser desorption ionization and unraveling of the mechanism for gas‐phase peptide ion formation

In a previous study on matrix‐assisted laser desorption ionization (MALDI) of peptides using α‐cyano‐4‐hydroxycinnamic acid (CHCA) as a matrix, we found that the patterns of single‐shot spectra obtained under different experimental conditions became similar upon temperature selection. In this paper, we report that absolute ion abundances are also similar in temperature‐selected MALDI spectra, even when laser fluence is varied. The result that has been obtained using CHCA and 2,5‐dihydroxybenzoic acid as matrices is in disagreement with the hypothesis of laser‐induced ionization of matrix as the mechanism for primary ion formation in MALDI. We also report that the total number of ions in such a spectrum is unaffected by the identity, concentration and number of analytes, i.e. it is the same as that in the spectrum of pure matrix. We propose that the generation of gas‐phase ions in MALDI can be explained in terms of two thermal reactions, i.e. the autoprotolysis of matrix molecules and the matrix‐to‐analyte proton transfer, both of which are in quasi‐equilibrium in the early matrix plume. Copyright © 2013 John Wiley & Sons, Ltd.     

Some new trends in the ionoluminescence of minerals

Ionoluminescence (IL) has mainly been used to detect impurities or defects inside synthetic materials. This paper gives a summary of new applications of IL to natural minerals that might be found in ancient pieces of jewellery or decorative artefacts (affreschi, stucchi, mosaics). Some relevant examples of its use for archaeometrical purposes are given to highlight the potential of the technique. Chemical information can be obtained by luminescent characterization of minerals. IL spectra act as digital imprint for elements or defects inside each material, enabling differentiation of natural specimens from imitations and/or synthetic analogues. Crystal field theory indicates it is the coordination number of the emitter inside the crystalline structure that gives information on its valence. Historical confusion between rubies and red spinel can easily be resolved by analysis of IL spectra. Modern synthetic diamonds can also be discriminated and blue sapphire can be distinguished from blue kyanite, a silicate that is currently being sold as its imitation. The technique can also differentiate between the synthetic and the natural gems. Polymorphs can be identified, and it is possible to recognize minerals from isomorphic series (from the same chemical group with the same structure) even when they share the same light emitter (e.g. Mn²⁺, in carbonates). High-quality glasses (e.g. laser glasses) which are normally used for faking gemstones can be also detected. We fully believe IL will, in the future, be a powerful technique for determining the crystallinity of solids. This paper gives an overview of possible applications of IL to archaeometry for mineral characterization; this is a new application that still requires further study.