PARAFASCA: ASCA combined with PARAFAC for the analysis of metabolic fingerprinting data

Novel post‐genomics experiments such as metabolomics provide datasets that are highly multivariate and often reflect an underlying experimental design, developed with a specific experimental question in mind. ANOVA‐simultaneous component analysis (ASCA) can be used for the analysis of multivariate data obtained from an experimental design instead of the widely used principal component analysis (PCA). This increases the interpretability of the model in terms of the experimental question. Aside from the levels of individual factors, variation that can be described by the experimental design may also depend on levels of multiple (crossed) factors simultaneously, e.g. the interactions. ASCA describes each contribution with a PCA model, but a contribution depending on crossed factors may be described more parsimoniously by multiway models like parallel factor analysis (PARAFAC). The combination of PARAFAC and ASCA, named PARAFASCA, provides a view on the data that is both parsimonious and focused on the experimental question. The novel method is used to analyze a dataset in which the effect of two doses of hydrazine on the urinary chemical composition of rats is investigated by time‐resolved metabolic fingerprinting with nuclear magnetic resonance (NMR) spectroscopy. This experiment has been conducted to monitor the dose‐specific urine composition changes in time upon hydrazine administration. Comparison of the PCA, the ASCA and the PARAFASCA models shows that ASCA and PARAFASCA describe the data more dedicated to the experimental question than PCA, but that PARAFASCA is more parsimonious than ASCA, and separates the variation underlying different effects better. Copyright © 2008 John Wiley & Sons, Ltd.     

Optical and X-ray Fluorescence Spectroscopy Studies of Bone and Teeth in Newborn Rats After Maternal Treatment with Indinavir

An experiment estimating influence of antiviral drug indinavir treatment during pregnancy on bones and teeth development in newborn rats was performed. Two different fluorescence noninvasive spectroscopy techniques, i.e . laser (407 nm)-induced fluorescence method to characterize the organic fluorescent molecules and X-ray fluorescence analysis to determine mineral components were used to study the surface response of femur, mandible and incisor during their formation in the first month of a rat's life. Differences in autofluorescence depending on the form of the bone were observed on the basis of the emission from enamel in 7-, 14- and 28-day-old newborn rats. The dependence between decrease in intensity of fluorescence and increase in mineralization with age in newborn rats was observed. An enhancement of the autofluorescence and a decrease in the concentration of Ca as a main element, as well as disturbances in the concentration of Zn as trace element were observed for bone as well as teeth in newborns during the first month of their life after maternal administration of indinavir (500 mg kg⁻¹ P.O.) in comparison with the control group. The results indicate that indinavir causes a delay in development of the skeleton and teeth in newborn rats.     

ANOVA–principal component analysis and ANOVA–simultaneous component analysis: a comparison

ANOVA–simultaneous component analysis (ASCA) is a recently developed tool to analyze multivariate data. In this paper, we enhance the explorative capability of ASCA by introducing a projection of the observations on the principal component subspace to visualize the variation among the measurements. We compare the significance of experimental effects for ASCA and ANOVA–principal component analysis (PCA), a similar tool to explore multivariate data, by using permutation tests. Furthermore, we quantify the quality of the loadings estimate obtained with ASCA and compare this with the loadings estimate obtained with ANOVA–PCA. Copyright © 2011 John Wiley & Sons, Ltd.     

Chemometric evaluation of different experimental conditions on wheat (Triticum aestivum L.) development using liquid chromatography mass spectrometry (LC–MS) profiles of benzoxazinone derivatives

Different chemometric techniques have been used to evaluate the effect of distinct experimental conditions and factors on Triticum aestivum L. plant development. The study was conducted using three wheat varieties, Astron, Ritmo and Stakado. These varieties were grown under organic and conventional cultivation systems. Samples were collected at five growth stages. Shoots and roots of each plant at these stages were analysed. Three replicates of each analysed sample were performed to improve representativeness and to allow for the evaluation of natural variability and interaction effects. All samples were analysed using Liquid Chromatography Mass–Spectrometry (LC–MS), and the Total Ion Current (TIC) profiles of benzoxazinone derivatives obtained for each sample were investigated. Qualitative and quantitative assessments of these TIC profiles and of their changes in the analysed samples were carried out using different chemometric techniques. Estimation of main effects, and of their possible interaction, was performed by means of Analysis of Variance combined to Principal Component Analysis (ANOVA–PCA) and of Analysis of Variance combined to Simultaneous Component Analysis (ASCA).     

Application of parallel factor analysis to total synchronous fluorescence spectrum of dilute multifluorophoric solutions: Addressing the issue of lack of trilinearity in total synchronous fluorescence data set

In recent years, total synchronous fluorescence (TSF) spectroscopy has become popular for the analysis of multifluorophoric systems. Application of PARAFAC, a popular deconvolution tool, requires trilinear structure in the three-way data array. The present work shows that TSF based three-way array data set of dimension sample × wavelength × Δλ does not have trilinear structure and hence it should not be subjected to PARAFAC analysis. This work also proposes that a TSF data set can be converted to an excitation–emission matrix fluorescence (EEMF) like data set which has trilinear structure, so that PARAFAC analysis can be performed on it. This also enables the retrieval of PARAFAC-separated component TSF spectra.     

Multivariate curve resolution applied to in situ X-ray absorption spectroscopy data: An efficient tool for data processing and analysis

Large datasets containing many spectra commonly associated with in situ or operando experiments call for new data treatment strategies as conventional scan by scan data analysis methods have become a time-consuming bottleneck. Several convenient automated data processing procedures like least square fitting of reference spectra exist but are based on assumptions. Here we present the application of multivariate curve resolution (MCR) as a blind-source separation method to efficiently process a large data set of an in situ X-ray absorption spectroscopy experiment where the sample undergoes a periodic concentration perturbation. MCR was applied to data from a reversible reduction–oxidation reaction of a rhenium promoted cobalt Fischer–Tropsch synthesis catalyst. The MCR algorithm was capable of extracting in a highly automated manner the component spectra with a different kinetic evolution together with their respective concentration profiles without the use of reference spectra. The modulative nature of our experiments allows for averaging of a number of identical periods and hence an increase in the signal to noise ratio (S/N) which is efficiently exploited by MCR. The practical and added value of the approach in extracting information from large and complex datasets, typical for in situ and operando studies, is highlighted.     

Trace enrichment, chromatographic separation and biodegradation of cytostatic compounds in surface water

A trace analytical procedure for the cytostatic drugs carmustine, chlorambucil, cisplatin, cyclophosphamide, cytarabine, etoposide, 5-fluorouracil, melphalan, methotrexate, and vinblastine was developed in order to evaluate the environmental hazards of these drugs in clinical waste water and sewage treatment plants. The analysis was performed using solid phase extraction with subsequent HPLC separation and quantitative determination by gradient elution techniques with DAD and fluorescence detection. Detection limits after the clean-up and enrichment procedure vary from 0.002 to 0.2 mg/L. A simulation of the degradation processes under conditions as close as possible to those in a real sewage plant showed that cisplatin and cyclophosphamide are not biodegradable, but cytarabine and 5-fluorouracil are biodegradable in different magnitudes. The biodegradation process of methotrexate is combined with the generation of the toxic and persistent degradation product 7-hydroxymethotrexate. Received: 27 August 1997 / Revised: 27 November 1997 / Accepted: 1 December 1997     

Trace enrichment, chromatographic separation and biodegradation of cytostatic compounds in surface water

A trace analytical procedure for the cytostatic drugs carmustine, chlorambucil, cisplatin, cyclophosphamide, cytarabine, etoposide, 5-fluorouracil, melphalan, methotrexate, and vinblastine was developed in order to evaluate the environmental hazards of these drugs in clinical waste water and sewage treatment plants. The analysis was performed using solid phase extraction with subsequent HPLC separation and quantitative determination by gradient elution techniques with DAD and fluorescence detection. Detection limits after the clean-up and enrichment procedure vary from 0.002 to 0.2 mg/L. A simulation of the degradation processes under conditions as close as possible to those in a real sewage plant showed that cisplatin and cyclophosphamide are not biodegradable, but cytarabine and 5-fluorouracil are biodegradable in different magnitudes. The biodegradation process of methotrexate is combined with the generation of the toxic and persistent degradation product 7-hydroxymethotrexate. Received: 27 August 1997 / Revised: 27 November 1997 / Accepted: 1 December 1997     

Steroid and steroid glucuronide profiles in urine during pregnancy determined by liquid chromatography–electrospray ionization-tandem mass spectrometry

An ultra performance liquid chromatography–electrospray ionization-tandem mass spectrometry (UPLC–MS/MS) method was developed for the analysis of steroids and their glucuronides in urine samples. The method provides high sensitivity and fast analysis, as both steroids and their glucuronides can be analyzed directly without hydrolysis or complex sample preparation. The method was applied in profiling of targeted and nontargeted steroids and steroid glucuronides during pregnancy. The concentrations of 11 of 27 targeted steroids and steroid glucuronides and the concentrations of 25 nontargeted steroid glucuronides increased about 10–400 fold during the pregnancy. The concentrations of most of these 36 compounds began to increase in the first days of the pregnancy, increased gradually during the pregnancy, achieved a maximum in late pregnancy, and decreased sharply after delivery. Exceptionally, the concentrations of allopregnanolone and 17-hydroxypregnenolone started to increase later than those of the other steroids. Moreover, the concentrations of E2 glucuronides began to decrease one week before the delivery, in contrast to most of the steroids and steroid glucuronides, whose concentrations dropped sharply during the delivery. Concentrations of 34 compounds decreased noticeably when the subject was on sick leave owing a series of painful contractions. The results suggest that steroids and especially steroid glucuronides may provide a valuable diagnostic tool to follow the course of pregnancy.     

The geometry of ASCA

For analyzing designed high‐dimensional data, no standard methods are currently available. A method that is becoming more and more popular for analyzing such data is ASCA. The mathematics of ASCA are already described elsewhere but a geometrical interpretation is still lacking. The geometry can help practitioners to understand what ASCA does and the more advanced user can get insight into the properties of the method. This paper shows the geometry of ASCA in both the row‐ and column‐space of the matrices involved. Copyright © 2008 John Wiley & Sons, Ltd.     

A flexible trilinear decomposition algorithm for three-way calibration based on the trilinear component model and a theoretical extension of the algorithm to the multilinear component model

There is a great deal of interest in decompositions of multilinear component models in the field of multi-way calibration, especially the three-way case. A flexible novel trilinear decomposition algorithm of the trilinear component model as a modification of an alternating least squares algorithm for three-way calibration is proposed. The proposed algorithm (constrained alternating trilinear decomposition, CATLD) is based on an alternating approximate least-squares scheme, in which two extra terms are added to each loss function, making it more efficient and flexible. The analysis of simulated three-way data arrays shows that it converges fast, is insensitive to initialization, and is insensitive to the overestimated number of components used in the decomposition. The analysis of real excitation–emission matrix (EEM) fluorescence and real high performance liquid chromatography–photodiode array detection (HPLC–DAD) data arrays confirms the results of the simulation studies, and shows that the proposed algorithm is favorable not only for EEMs but also for HPLC–DAD data. The three-way calibration method based on the CATLD algorithm is very efficient and flexible for direct quantitative analysis of multiple analytes of interest in complex systems, even in the presence of uncalibrated interferents and varying background interferents. Additionally, a theoretical extension of the proposed algorithm to the multilinear component model (constrained alternating multilinear decomposition, CAMLD) is developed.     

Evaluation of the feasibility of the electronic tongue as a rapid analytical tool for wine age prediction and quantification of the organic acids and phenolic compounds. The case-study of Madeira wine

A set of fourteen Madeira wines comprising wines produced from four Vitis vinifera L. varieties (Bual, Malvasia, Verdelho and Tinta Negra Mole) that were 3, 6, 10 and 17 years old was analysed using HPLC and an electronic tongue (ET) multisensor system. Concentrations of 24 organic acids, phenolic and furanic compounds were determined by HPLC. The ET consisting of 26 potentiometric chemical sensors with plasticized PVC and chalcogenide glass membranes was used. Significance of the effects of age and variety on the ET response and wine composition with respect to the organic acids, phenolics and furanic derivatives were evaluated using ANOVA—Simultaneous Component Analysis (ASCA). Significance of the effects was estimated using a permutation test (1000 permutations). It was found that effects of age, grape variety and their interaction were significant for the HPLC data set and only the effect of age was significant for the ET data. Calibration models of the HPLC and ET data with respect to the wine age and of the ET data with respect to the concentration of the organic acids and phenolics were calculated using PLS1 regression. Models were validated using cross-validation. It was possible to predict wine age from HPLC and ET data with the accuracy in cross-validation of 2.6 and 1.8 years respectively. The ET was capable of detecting the following components (mean relative error in cross-validation is shown in the parentheses): tartaric (8%), citric (5%), formic (12%), protocatehuic (5%), vanillic (18%) and sinapic (14%) acids, catechin (6%), vanillin (12%) and trans-resveratrol (5%). The ET capability of predicting Madeira wine age with good accuracy (1.8 years) as well as quantify of some organic acids and phenolic compounds was demonstrated.     

WE-ASCA: The Weighted-Effect ASCA for Analyzing Unbalanced Multifactorial Designs—A Raman Spectra-Based Example

Analyses of multifactorial experimental designs are used as an explorative technique describing hypothesized multifactorial effects based on their variation. The procedure of analyzing multifactorial designs is well established for univariate data, and it is known as analysis of variance (ANOVA) tests, whereas only a few methods have been developed for multivariate data. In this work, we present the weighted-effect ASCA, named WE-ASCA, as an enhanced version of ANOVA-simultaneous component analysis (ASCA) to deal with multivariate data in unbalanced multifactorial designs. The core of our work is to use general linear models (GLMs) in decomposing the response matrix into a design matrix and a parameter matrix, while the main improvement in WE-ASCA is to implement the weighted-effect (WE) coding in the design matrix. This WE-coding introduces a unique solution to solve GLMs and satisfies a constrain in which the sum of all level effects of a categorical variable equal to zero. To assess the WE-ASCA performance, two applications were demonstrated using a biomedical Raman spectral data set consisting of mice colorectal tissue. The results revealed that WE-ASCA is ideally suitable for analyzing unbalanced designs. Furthermore, if WE-ASCA is applied as a preprocessing tool, the classification performance and its reproducibility can significantly improve.     

Comparison of Multivariate ANOVA-Based Approaches for the Determination of Relevant Variables in Experimentally Designed Metabolomic Studies

The use of chemometric methods based on the analysis of variances (ANOVA) allows evaluation of the statistical significance of the experimental factors used in a study. However, classical multivariate ANOVA (MANOVA) has a number of requirements that make it impractical for dealing with metabolomics data. For this reason, in recent years, different options have appeared that overcome these limitations. In this work, we evaluate the performance of three of these multivariate ANOVA-based methods (ANOVA simultaneous component analysis—ASCA, regularized MANOVA–rMANOVA, and Group-wise ANOVA-simultaneous component analysis—GASCA) in the framework of metabolomics studies. Our main goals are to compare these various ANOVA-based approaches and evaluate their performance on experimentally designed metabolomic studies to find the significant factors and identify the most relevant variables (potential markers) from the obtained results. Two experimental data sets were generated employing liquid chromatography coupled to mass spectrometry (LC-MS) with different complexity in the design to evaluate the performance of the statistical approaches. Results show that the three considered ANOVA-based methods have a similar performance in detecting statistically significant factors. However, relevant variables pointed by GASCA seem to be more reliable as there is a strong similarity with those variables detected by the widely used partial least squares discriminant analysis (PLS-DA) method.     

Hasse diagram technique as a tool for water quality assessment

The management of the quality large water catchments is a complex problem which requires intelligent data analysis on various levels – analytical, spatial, and temporal. Recently, a successful approach is developed combining advanced multivariate data treatment approaches like self-organizing maps of Kohonen (SOM) and Hasse diagram technique (HDT). In the first step of the environmetric analysis the monitoring data were subject to pre-processing using SOMs to reduce the number of objects and/or water quality parameters. In the next step HDT for partial ranking (both in spatial and temporal aspect) was applied according to the pre-selected set of the water quality parameters. The use of the water quality norms issued by the Bulgarian environmental authorities revealed important details in assessing the Maritsa River water quality. Thus, the relations between different water quality patterns and sampling stations could be used by water management authorities during the period of observation.     

Morus alba Prevented the Cyclophosphamide Induced Somatic and Germinal Cell Damage in Male Rats by Ameliorating the Antioxidant Enzyme Levels

Cytogenetic analysis is essential to determine the effect of mutagens and antimutagens on genetic material. This study was done to evaluate the protective effect of root bark extract of Morus alba (M. alba) against cyclophosphamide induced somatic and germinal cell damage in male rats. The ethanolic extract of M. alba (0.25, 0.5 and 1 g/kg, 2 weeks) was evaluated against cyclophosphamide (75 mg/kg, single dose) induced nuclear damage. The sampling was done after 48 h of the clastogen treatment. The somatic and germinal nuclear damage was studied by bone marrow micronucleus and sperm analysis, respectively. Serum superoxide and catalase levels were estimated to determine the antioxidant status in each group. The results were analyzed statistically to find the significant variation. The administration of M. alba for 2 weeks suppressed dose-dependently the changes induced by cyclophosphamide. M. alba (0.5 g/kg) decreased the frequency of micronucleated erythrocyte, sperm shape abnormality and enhanced the sperm count, sperm motility and polychromatic-normochromatic erythrocytes ratio significantly (p < 0.05) in comparison with the cyclophosphamide treated group. The highest tested dose of M. alba (1 g/kg) produced more prominent suppression (p < 0.01) in the cyclophosphamide-induced somatic and germinal cell defects. The results also showed significant (p < 0.05) improvement in the serum antioxidant enzymes levels with M. alba when compared with the challenge group. The lower dose of M. alba extract (0.25 g/kg) prevented the CP-induced changes but was found to be statistically insignificant. Therefore, antimutagenic potential of the high dose of the extract of M. alba is possibly due to its antioxidant nature. The ability of the M. alba extract to prevent the nuclear damage could play an important role in overcoming several mutational defects that are associated with anticancer chemotherapy.     

Dentin Phosphoprotein Mimetic Peptide Nanofibers Promote Biomineralization

Dentin phosphoprotein (DPP) is a major component of the dentin matrix playing crucial role in hydroxyapatite deposition during bone mineralization, making it a prime candidate for the design of novel materials for bone and tooth regeneration. The bioactivity of DPP‐derived proteins is controlled by the phosphorylation and dephosphorylation of the serine residues. Here an enzyme‐responsive peptide nanofiber system inducing biomineralization is demonstrated. It closely emulates the structural and functional properties of DPP and facilitates apatite‐like mineral deposition. The DPP‐mimetic peptide molecules self‐assemble through dephosphorylation by alkaline phosphatase (ALP), an enzyme participating in tooth and bone matrix mineralization. Nanofiber network formation is also induced through addition of calcium ions. The gelation process following nanofiber formation produces a mineralized extracellular matrix like material, where scaffold properties and phosphate groups promote mineralization. It is demonstrated that the DPP‐mimetic peptide nanofiber networks can be used for apatite‐like mineral deposition for bone regeneration.     

31P NMR and HPLC Investigations of the Cyclophosphamide Metabolite,Phosphoramide Mustard

Abstract

Phosphoramide mustard (PM), a key active metabolite of the widely used anticancer drug cyclophosphamide (CP), can exist in several closely-related ionized, cyclized and substituted forms. We have developed a high pressure liquid chromatographic (HPLC) method for analysing serum concentrations of PM in order to relate these serum concentrations to toxicity and efficacy of treatment of CP. ³¹p NMR spectroscopy is used to verify the HPLC peak homology of the proposed PM peak.     

Nematic ordered cellulose templates mediating order-patterned deposition accompanied with synthesis of calcium phosphates

In a previous study, the nematic ordered cellulose (NOC) templates successfully induced biodirected epitaxial nanodeposition of cellulose nanofibers secreted by Gluconacetobacter xylinus along the orientation of the molecular tracks (Kondo et al. 2002). As an extended concept for the NOC, this article attempts to propose a sort of biomimic mineralization using the template. It combines morphologically controlling process with synthesis of the calcium phosphate as a major component of bones. This process was initially mediated by the modified NOC template having a pair of roles of the ion supply sources and scaffolds for 3D-ordering architecture of the calcium phosphate as a biomineral in the key functions for biomineralization. The successful establishment of such an ordered deposition of the inorganic on the template was confirmed by several surface characterizations such as atomic force microscopy, X-ray photoelectron spectroscopy, scanning electron microscopy, and so on. Moreover, similarly to human bones, the obtained major assemble states of the calcium phosphates exhibited amorphous. The above process using the bifunctional cellulose template can be considered as a biomimic mineralization, which also opens pathways toward preparation of potentially versatile organic–inorganic order-patterned composites under a less energy consumption.     

吖啶橙-细胞DNA荧光抑制法筛选抗癌药物

在DNA荧光法‘’‘初步筛选抗癌药物的实验中,漠化乙锭（EB）是常用的荧光探针,其本身荧光板弱,但能与双链DNA发生专一性插入作用,使荧光大幅度地增强．但EB不能进入完整的细胞膜［’j．对陕橙（AO）常用于细胞内DNA和RNA的定量测定,并能用于活细胞染色;AO与核酸的结合方式有2种：一种是在嵌入核酸双链的碱基对之间形成AO－DNA复合物,另一种是与单链核酸的磷酸发生静电间相互作用,形成AO－RNA复合物．如用蓝光激发,前者发射峰波长为530urn的绿色荧光,后者发射峰波长为640urn的红色荧卅’‘．本文提出一种对细胞周期非…