Milan Meloun

Critical comparison of methods predicting the number of components in spectroscopic data

Determining the number of chemical components in a mixture is a first important step to further analysis in spectroscopy. The accuracy of 13 statistical indices for estimation of the number of components that contribute to spectra was critically tested on simulated and on experimental data sets using algorithm INDICES in S-Plus. All methods are classified into two categories, precise methods based upon a knowledge of the instrumental error of the absorbance data, sinst (A), and approximate methods requiring no such knowledge. Most indices always predict the correct number of components even a presence of the minor one when the signal-to-error ratio (SER) is higher than 10 but in case of RESO and IND higher than 6. On base of SER the detection limit of every index method is estimated. Two indices, RESO and IND, correctly predict a minor component in a mixture even if its relative concentration is 0.5‐1% and solve an ill-defined problem with severe collinearity. For more than four components in a mixture the modifications of Elbergali et al. represent a useful resolution tool of a correct number of components in spectra for all indices. The Wernimont‐Kankare procedure performs reliable determination of the instrumental standard deviation of spectrophotometer used. In case of real experimental data the RESO, IND and indices methods based on knowledge of instrumental error should be preferred.

Evaluation of oxidative stress and inflammation in obese adults with metabolic syndrome

Abstract Background: Obesity and metabolic syndrome increase the risk of cardiovascular morbidity and mortality. Oxidative stress seems to be involved in the pathophysiology of diabetes and cardiovascular complications of metabolic syndrome. The aim of our study was to evaluate the level of oxidative stress and inflammation in obese adults with and without metabolic syndrome. Methods: Oxidative stress and inflammation markers (total amount of free radicals, malondialdehyde, allantoin, α1-antiproteinase, oxidized/reduced glutathione ratio, high-sensitive C-reactive protein, fibrinogen), total antioxidant capacity and lipid standardized α-tocopherol were determined in obese subjects fulfilling at least three criteria of metabolic syndrome according to the National Cholesterol Education Program-Adult Treatment Panel III guidelines (n=20 patients), in obese subjects without metabolic syndrome (n=20 patients) and in 48 healthy controls. Results: Oxidative stress and inflammation markers were significantly elevated in the obese subjects, especially in those exhibiting metabolic syndrome. According to multidimensional statistical analysis, oxidative stress was independently related to triacylglyceride concentration, abdominal fat, low high-density lipoprotein cholesterol and low lipid standardized α-tocopherol in the patients with metabolic syndrome. Conclusions: High levels of free radicals together with low antioxidant capacity detected in obese adults indicate elevated oxidative stress, which is – together with systemic inflammation – further potentiated in the case of obese patients with metabolic syndrome. This imbalance in oxidative/antioxidative status and subclinical inflammatory state leads to higher risk of atherosclerotic and diabetic complications. Clin Chem Lab Med 2008;46:499–505.

Steroid metabolome in plasma from the umbilical artery, umbilical vein, maternal cubital vein and in amniotic fluid in normal and preterm labor.

The boost in placental production of CRH in late pregnancy is specific for human. CRH receptors are expressed in the fetal zone of the fetal adrenal (FZFA). Hence, we evaluated the associations between the steroid metabolome and gestational age (GA). The levels of 69 steroids and steroid polar conjugates such as 3beta-hydroxy-5-ene steroids (3betaOH5S), 3-oxo-4-ene steroids (3O4S), progesterone 5alpha/beta-reduced metabolites, 20alpha-hydroxy-metabolites of C21 steroids, C19 5alpha/beta-reduced metabolites, 7alpha/beta-hydroxy-metabolites of 3betaOH5S, estrogens and 16alpha-hydroxy-metabolites of 3betaOH5S and 3O4S, were measured by GC-MS in plasma from the umbilical artery (UA), umbilical vein (UV), and maternal cubital vein (MV) and in amniotic fluid (AF) in 12 women at normal labor and 38 women at preterm labor due to pathologies unrelated to steroid status. Using multivariate regression, prediction models for GA were completed for the individual body fluids. The conjugated 3betaOH5S (the key products of the FZFA), estrogens, some polar conjugates of progesterone 5alpha/beta-reduced metabolites and some steroid 7alpha/beta- and 16alpha-hydroxy-metabolites showed strong positive correlations with the GA. The predictivity decreased in the following sequence UV (R=0.950), UA (R=0.945), MV (R=0.895), and AF (R=0.891). Although the predictivity of steroids in maternal blood was slightly less effective when compared with the UV and UA, it was the best solution for further practice.

Multiparametric curve fitting--X: a structural classification of programs for analysing multicomponent spectra and their use in equilibrium-model determination.

A functional structure-classification of programs for analysis of spectra elucidates their efficiency for determination of the stoichiometric indices, stability constants and molar absorptivities of complex species. SQUAD (84) introduces new functional units for (i) determination of the number of light-absorbing species, (ii) a rigorous fitness test, (iii) plotting three-dimensional graphs of a paraboloid minimum response-surface as a function of two selected parameters, and a graph of the fitted absorbance response-plane, (iv) simultaneous estimation of stoichiometric indices and stability constants, (v) simulation of an absorbance matrix data by loading with random errors related to the instrumental variance of the absorbance. A guide to experimental procedure and computational strategy for chemical model determination is given and nine diagnostic tools useful in finding the number of species present and their stoichiometry and stability constants by regression analysis of spectra are tested, by use of literature data.

Transformation in the PC-Aided Biochemical Data Analysis

Abstract Data transformations enable expression of original data in a new scale, more suitable for data analysis. In computer-aided interactive analysis of biochemical and clinical data an exploratory data analysis often finds that the sample distribution is systematically skewed or does not accept a sample homogeneity. Under such circumstances the original data should be transformed. The power transformation and the Box-Cox transformation improve sample symmetry and also stabilize variance. Both the Hines-Hines selection graph and the plot of logarithm of a maximum likelihood function allow selection of an optimum transformation parameter. The proposed procedure of data transformation in univariate data analysis is illustrated on a determination of 17-hydroxypregnenolone in umbilical blood of a population of newborns. Lower levels of free 5-ene steroids in umbilical blood and elevated levels of 5-ene steroid sulfates indicate a congenital sex-specific placental sulfatase insufficiency. After examination of statistical assumptions by diagnostic plots of an exploratory data analysis the best estimate of a mean value of 17-hydroxypregnenolone is derived.

Detection of single influential points in OLS regression model building

Identifying outliers and high-leverage points is a fundamental step in the least-squares regression model building process. Various influence measures based on different motivational arguments, and designed to measure the influence of observations on different aspects of various regression results, are elucidated and critiqued here. On the basis of a statistical analysis of the residuals (classical, normalized, standardized, jackknife, predicted and recursive) and diagonal elements of a projection matrix, diagnostic plots for influential points indication are formed. Regression diagnostics do not require a knowledge of an alternative hypothesis for testing, or the fulfillment of the other assumptions of classical statistical tests. In the interactive, PC-assisted diagnosis of data, models and estimation methods, the examination of data quality involves the detection of influential points, outliers and high-leverages, which cause many problems in regression analysis. This paper provides a basic survey of the influence statistics of single cases combining exploratory analysis of all variables. The graphical aids to the identification of outliers and high-leverage points are combined with graphs for the identification of influence type based on the likelihood distance. All these graphically oriented techniques are suitable for the rapid estimation of influential points, but are generally incapable of solving problems with masking and swamping. The powerful procedure for the computation of influential points characteristics has been written in Matlab 5.3 and is available from authors.

The thermodynamic dissociation constants of ambroxol, antazoline, naphazoline, oxymetazoline and ranitidine by the regression analysis of spectrophotometric data

The mixed dissociation constants of five drug acids-ambroxol, antazoline, naphazoline, oxymetazoline and ranitidine-at various ionic strengths I of range 0.01 and 1.0 and at temperatures of 25 and 37 degrees C were determined using SQUAD(84) regression analysis of the pH-spectrophotometric titration data. A proposed strategy of efficient experimentation in a protonation constants determination, followed by a computational strategy for the chemical model with a protonation constants determination, is presented on the protonation equilibria of ambroxol. The thermodynamic dissociation constant pK(a)(T) was estimated by non-linear regression of {pK(a), I} data at 25 and 37 degrees C: for ambroxol p K (a ,1)(T )=8.05 (6) and 8.25 (4), logbeta (21)(T )=11.67 (6) and 11.83 (8), for antazoline p K (a ,1)(T )=7.79 (2) and 7.83 (6), p K (a ,2)(T )=9.74 (3) and 9.55 (2), for naphazoline pK (a ,1)(T )=10.81 (1) and 10.63 (1), for oxymethazoline pK (a ,1)(T )=10.62 (2) and 10.77 (7), pK(a,2)(T)=12.03(3) and 11.82 (4) and for ranitidine p K (a ,1)(T )=1.89 (1) and 1.77 (1). Goodness-of-fit tests for various regression diagnostics enabled the reliability of the parameter estimates to be found.

Neuroactive steroids, their precursors and polar conjugates during parturition and postpartum in maternal blood: 2. Time profiles of pregnanolone isomers

Time profiles of the pregnanolone isomers epipregnanolone (3 beta-hydroxy-5 beta-pregnan-20-one), allopregnanolone (3 alpha-hydroxy-5 alpha-pregnan-20-one), pregnanolone (3 alpha-hydroxy-5 beta-pregnan-20-one), and isopregnanolone (3 beta-hydroxy-5 alpha-pregnan-20-one) were measured around parturition and in the postpartum period in the serum of 13 and three women with subarachnoidal and epidural analgesia, respectively. In addition, the levels of polar conjugates of all pregnanolone isomers were followed during parturition. GC/MS analysis was used for the measurement of steroid levels. Changes in concentrations of free steroids exhibited a similar pattern, with a fall primarily within the first hour after delivery. The decrease in conjugated steroids was shifted to the interval within the first hour and first day after delivery, and the changes were more pronounced. The time profile of the conjugated/free steroid ratio exhibited a significant decrease within the first hour and the first day after delivery in all of the isomers investigated. A decrease was also observed in the ratio of 3 alpha/3 beta-isomers and 5 alpha/5 beta-isomers around parturition. The possible physiological consequences of the findings are indicated.

New methodology of influential point detection in regression model building for the prediction of metabolic clearance rate of glucose

Abstract Identifying outliers and high-leverage points is a fundamental step in the least-squares regression model building process. The examination of data quality involves the detection of influential points, outliers and high-leverages, which cause many problems in regression analysis. On the basis of a statistical analysis of the residuals (classical, normalized, standardized, jackknife, predicted and recursive) and diagonal elements of a projection matrix, diagnostic plots for influential points indication are formed. The identification of outliers and high leverage points are combined with graphs for the identification of influence type based on the likelihood distance. The powerful procedure for the computation of influential points characteristics written in S-Plus is demonstrated on the model predicting the metabolic clearance rate of glucose (MCRg) that represents the ratio of the amount of glucose supplied to maintain blood glucose levels during the euglycemic clamp and the blood glucose concentration from common laboratory and anthropometric indices. MCRg reflects insulin sensitivity filtering-off the effect of blood glucose. The prediction of clamp parameters should enable us to avoid the demanding clamp examination, which is connected with a higher load and risk for patients.

Determination of the number of light-absorbing species in the protonation equilibra of selected drugs

The determination of the number of components in a mixture is an important tool for qualitative and quantitative analysis in spectroscopy. The accuracy of nine selected indices for an estimation of the number of components that contribute to a set of spectra was critically tested on experimental data sets of protonation equilibria of four drugs using the INDICES algorithm in S-Plus. Methods are classified into two categories: precise methods based on a knowledge of the instrumental error of the sabsorbance data, sinst(A), and approximate methodsrequiring no such knowledge. Indices of precise methods predict the correct number of components, even the presence of a minor one, when the quality of data is high and instrumental error is known. Improved identification of the number of species uses the second or third derivative function for some indices, namely when the number of species in the mixture is higher than four and when, due to large variations in the indicator values even at logarithmic scale, the indicator curve does not reach an obvious point where the slope changes. The number of variously protonated components and their dissociation constants for four drugs—mycophenolate, ambroxol, silybin and silydianin—at 25 ◦ C were determined using SQUAD(84) regression and INDICES principal component analysis of the pH-spectrophotometric data. A proposed strategy of efficient experimentation in protonation constants determination, followed by a computational strategy, is presented with the goodness-of-fit tests for various regression diagnostics enabling the reliability of parameter estimates to be accessed.