A computer-aided quantitative method for a complex analysis of gel electrophoretograms is presented. The analysis consists of several steps: (i) determination of the background image by methods of mathematical morphology and its subtraction from the gel image, (ii) selection of an appropriate part of the gel lane including curved lanes and lanes with a nonuniform width, (iii) computation of the lane densitogram by averaging several lane-parallel scans, (iv) decomposition of the lane densitogram into component bands using a data selecting algorithm and Marquardt's minimizer. Several different functions for component bands are utilized. It is shown that the densitogram can be decomposed into component bands with reasonable accuracy only if an appropriate model function is chosen. The algorithms are tested on several different gel electrophoretograms which show typical features as a nonuniform background, curved lanes, an asymmetrical band shape and a superposition of small bands on the shoulders of big ones. It is shown that overlapped bands are best approximated by an asymmetrical Gausian curve and an asymmetrical Gauss-Cauchy function. Linear response to the serial dilution of the protein sample is tested.

• MeSH
• denzitometrie MeSH
• DNA bakterií analýza   MeSH
• elektroforéza v agarovém gelu metody   MeSH
• elektroforéza v polyakrylamidovém gelu metody   MeSH
• Escherichia coli genetika   MeSH
• matematika MeSH
• metoda nejmenších čtverců * MeSH
• molekulová hmotnost MeSH
• plazmidy MeSH
• počítačové zpracování obrazu * MeSH
• proteiny chemie   MeSH
• ribozomální proteiny analýza   MeSH
• Streptomyces aureofaciens chemie   MeSH
• Publikační typ
• časopisecké články MeSH
• Názvy látek
• DNA bakterií MeSH
• proteiny MeSH
• ribozomální proteiny MeSH

In the realm of multi-class classification, the twin K-class support vector classification (Twin-KSVC) generates ternary outputs {-1,0,+1} by evaluating all training data in a "1-versus-1-versus-rest" structure. Recently, inspired by the least-squares version of Twin-KSVC and Twin-KSVC, a new multi-class classifier called improvements on least-squares twin multi-class classification support vector machine (ILSTKSVC) has been proposed. In this method, the concept of structural risk minimization is achieved by incorporating a regularization term in addition to the minimization of empirical risk. Twin-KSVC and its improvements have an influence on classification accuracy. Another aspect influencing classification accuracy is feature selection, which is a critical stage in machine learning, especially when working with high-dimensional datasets. However, most prior studies have not addressed this crucial aspect. In this study, motivated by ILSTKSVC and the cardinality-constrained optimization problem, we propose ℓp-norm least-squares twin multi-class support vector machine (PLSTKSVC) with 0

• Klíčová slova
• -norm, Cardinality-constrained optimization problem, Feature selection, Least-squares, Multi-class classification, Twin k-class support vector classification,
• MeSH
• metoda nejmenších čtverců MeSH
• strojové učení * MeSH
• support vector machine * MeSH
• Publikační typ
• časopisecké články MeSH

When drugs are poorly soluble then, instead of the potentiometric determination of dissociation constants, pH-spectrophotometric titration can be used along with nonlinear regression of the absorbance response surface data. Generally, regression models are extremely useful for extracting the essential features from a multiwavelength set of data. Regression diagnostics represent procedures for examining the regression triplet (data, model, method) in order to check (a) the data quality for a proposed model; (b) the model quality for a given set of data; and (c) that all of the assumptions used for least squares hold. 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, that cause many problems when regression fitting the absorbance response hyperplane. All graphically oriented techniques are suitable for the rapid estimation of influential points. The reliability of the dissociation constants for the acid drug silybin may be proven with goodness-of-fit tests of the multiwavelength spectrophotometric pH-titration data. The uncertainty in the measurement of the pK (a) of a weak acid obtained by the least squares nonlinear regression analysis of absorption spectra is calculated. The procedure takes into account the drift in pH measurement, the drift in spectral measurement, and all of the drifts in analytical operations, as well as the relative importance of each source of uncertainty. The most important source of uncertainty in the experimental set-up for the example is the uncertainty in the pH measurement. The influences of various sources of uncertainty on the accuracy and precision are discussed using the example of the mixed dissociation constants of silybin, obtained using the SQUAD(84) and SPECFIT/32 regression programs.

• MeSH
• antioxidancia analýza   chemie   MeSH
• časové faktory MeSH
• chemické modely MeSH
• koncentrace vodíkových iontů MeSH
• léčivé přípravky chemie   MeSH
• metoda nejmenších čtverců * MeSH
• regresní analýza * MeSH
• senzitivita a specificita MeSH
• silibinin MeSH
• silymarin analýza   chemie   MeSH
• spektrofotometrie metody   MeSH
• stabilita léku MeSH
• titrace metody   MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• Názvy látek
• antioxidancia MeSH
• léčivé přípravky MeSH
• silibinin MeSH
• silymarin MeSH

The common approach for regression analysis with compositional variables is to express compositions in log-ratio coordinates (coefficients) and then perform standard statistical processing in real space. Similar to working in real space, the problem is that the standard least squares regression fails when the number of parts of all compositional covariates is higher than the number of observations. The aim of this study is to analyze in detail the partial least squares (PLS) regression which can deal with this problem. In this paper, we focus on the PLS regression between more than one compositional response variable and more than one compositional covariate. First, we give the PLS regression model with log-ratio coordinates of compositional variables, then we express the PLS model directly in the simplex. We also prove that the PLS model is invariant under the change of coordinate system, such as the ilr coordinates with a different contrast matrix or the clr coefficients. Moreover, we give the estimation and inference for parameters in PLS model. Finally, the PLS model with clr coefficients is used to analyze the relationship between the chemical metabolites of Astragali Radix and the plasma metabolites of rat after giving Astragali Radix.

• Klíčová slova
• 62H12, 62H86, 62J05, Compositional data, centered log-ratio coefficients, coordinates, linear regression model, partial least squares,
• Publikační typ
• časopisecké články MeSH

Potentiometric and spectrophotometric pH-titration of the multiprotic cytostatics bosutinib for dissociation constants determination were compared. Bosutinib treats patients with positive chronic myeloid leukemia. Bosutinib exhibits four protonatable sites in a pH range from 2 to 11, where two pK are well separated (ΔpK>3), while the other two are near dissociation constants. In the neutral medium, bosutinib occurs in the slightly water soluble form LH that can be protonated to the soluble cation LH4(3+). The molecule LH can be dissociated to still difficultly soluble anion L(-). The set of spectra upon pH from 2 to 11 in the 239.3-375.0nm was divided into two absorption bands: the first one from 239.3 to 290.5nm and the second from 312.3 to 375.0nm, which differ in sensitivity of chromophores to a pH change. Estimates of pK of the entire set of spectra were compared with those of both absorption bands. Due to limited solubility of bosutinib the protonation in a mixed aqueous-methanolic medium was studied. In low methanol content of 3-6% three dissociation constants can be reliably determined with SPECFIT/32 and SQUAD(84) and after extrapolation to zero content of methanol they lead to pKc1=3.43(12), pKc2=4.54(10), pKc3=7.56(07) and pKc4=11.04(05) at 25°C and pKc1=3.44(06), pKc2=5.03(08) pKc3=7.33(05) and pKc4=10.92(06) at 37°C. With an increasing content of methanol in solvent the dissociation of bosutinib is suppressed and the percentage of LH3(2+) decreases and LH prevails. From the potentiometric pH-titration at 25°C the concentration dissociation constants were estimated with ESAB pKc1=3.51(02), pKc2=4.37(02), pKc3=7.97(02) and pKc4=11.05(03) and with HYPERQUAD: pKc1=3.29(12), pKc2=4.24(10), pKc3=7.95(07) and pKc4=11.29(05).

• Klíčová slova
• Bosutinib, Dissociation constants, ESAB2M, HYPERQUAD, INDICES, PALLAS, Potentiometric Titration, SQUAD(84) SPECFIT/32, Spectrophotometric titration,
• MeSH
• aniliny analýza   chemie   MeSH
• chinoliny analýza   chemie   MeSH
• cytostatické látky analýza   chemie   MeSH
• koncentrace vodíkových iontů MeSH
• metoda nejmenších čtverců MeSH
• nelineární dynamika * MeSH
• nitrily analýza   chemie   MeSH
• potenciometrie MeSH
• spektrofotometrie metody   MeSH
• Publikační typ
• časopisecké články MeSH
• Názvy látek
• aniliny MeSH
• bosutinib MeSH Prohlížeč
• chinoliny MeSH
• cytostatické látky MeSH
• nitrily MeSH

The mixed dissociation constants of four non-steroidal anti-inflammatory drugs (NSAIDs) ibuprofen, diclofenac sodium, flurbiprofen and ketoprofen at various ionic strengths I of range 0.003-0.155, and at temperatures of 25 degrees C and 37 degrees C, were determined with the use of two different multiwavelength and multivariate treatments of spectral data, SPECFIT/32 and SQUAD(84) nonlinear regression analyses and INDICES factor analysis. The factor analysis in the INDICES program predicts the correct number of components, and even the presence of minor ones, when the data quality is high and the instrumental error is known. The thermodynamic dissociation constant pK(a)(T) was estimated by nonlinear regression of (pK(a), I) data at 25 degrees C and 37 degrees C. Goodness-of-fit tests for various regression diagnostics enabled the reliability of the parameter estimates found to be proven. PALLAS, MARVIN, SPARC, ACD/pK(a) and Pharma Algorithms predict pK(a) being based on the structural formulae of drug compounds in agreement with the experimental value. The best agreement seems to be between the ACD/pK(a) program and experimentally found values and with SPARC. PALLAS and MARVIN predicted pK(a,pred) values with larger bias errors in comparison with the experimental value for all four drugs.

• MeSH
• antiflogistika nesteroidní chemie   MeSH
• chemické modely MeSH
• koncentrace vodíkových iontů MeSH
• metoda nejmenších čtverců MeSH
• molekulární struktura MeSH
• nelineární dynamika MeSH
• rozpustnost MeSH
• spektrofotometrie metody   MeSH
• termodynamika * MeSH
• titrace metody   MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• Názvy látek
• antiflogistika nesteroidní MeSH

The mixed dissociation constants of four anticancer drugs--camptothecine, 7-ethyl-10-hydroxycamptothecine, 10-hydroxycamptothecine and 7-ethylcamptothecine, including diprotic and triprotic molecules at various ionic strengths I of range 0.01 and 0.4, and at temperatures of 25 and 37 degrees C--were determined with the use of two different multiwavelength and multivariate treatments of spectral data, SPECFIT32 and SQUAD(84) nonlinear regression analyses and INDICES factor analysis. A proposed strategy for dissociation constants determination is presented on the acid-base equilibria of camptothecine. Indices of precise modifications of the factor analysis in the program INDICES predict the correct number of components, and even the presence of minor ones, when the data quality is high and the instrumental error is known. The thermodynamic dissociation constant pK(a)(T) was estimated by nonlinear regression of {pK(a), I} data at 25 and 37 degrees C: for camptothecine pK(a,1)(T)=2.90(7) and 3.02(8), pK(a,2)(T)=10.18(30) and 10.23(8); for 7-ethyl-10-hydroxycamptothecine, pK(a,1)(T)=3.11(2) and 2.46(6), pK(a,2)(T)=8.91(4) and 8.74(3), pK(a,3)(T)=9.70(3) and 9.47(8); for 10-hydroxycamptothecine pK(a,1)(T)=2.93(4) and 2.84(5), pK(a,2)(T)=8.93(2) and 8.92(2), pK(a,3)(T)=9.45(10) and 9.98(4); and for 7-ethylcamptothecine pK(a,1)(T)=3.10(4) and 3.30(16), pK(a,2)(T)=9.94(9) and 10.98(18). Goodness-of-fit tests for various regression diagnostics enabled the reliability of the parameter estimates found to be proven. Pallas and Marvin predict pK(a) being based on the structural formulae of drug compounds in agreement with the experimental value.

• MeSH
• fytogenní protinádorové látky chemie   MeSH
• irinotekan MeSH
• kamptothecin analogy a deriváty   chemie   MeSH
• koncentrace vodíkových iontů MeSH
• metoda nejmenších čtverců MeSH
• spektrofotometrie ultrafialová MeSH
• termodynamika MeSH
• titrace MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• Názvy látek
• 10-hydroxycamptothecin MeSH Prohlížeč
• 7-ethylcamptothecin MeSH Prohlížeč
• fytogenní protinádorové látky MeSH
• irinotekan MeSH
• kamptothecin MeSH

Estimation of nonlinear regression quality leads to examination of quality of parameter estimates, a degree of fit, a prediction ability of model proposed and quality of experimental data. Statistical analysis serves for computation of confidence intervals of parameters and confidence bands, the bias of parameters and bias of residuals. Goodness-of-fit test examines classical residuals using various diagnostics and identifies influential points. Mentioned topics of nonlinear model building and testing contained in MINOPT program from CHEMSTAT package are illustrated.

• Publikační typ
• časopisecké články MeSH

The objective of this study is the evaluation of the potential of high-throughput direct analysis in real time-high resolution mass spectrometry (DART-HRMS) fingerprinting and multivariate regression analysis in prediction of the extent of acrylamide formation in biscuit samples prepared by various recipes and baking conditions. Information-rich mass spectral fingerprints were obtained by analysis of biscuit extracts for preparation of which aqueous methanol was used. The principal component analysis (PCA) of the acquired data revealed an apparent clustering of samples according to the extent of heat-treatment applied during the baking of the biscuits. The regression model for prediction of acrylamide in biscuits was obtained by partial least square regression (PLSR) analysis of the data matrix representing combined positive and negative ionization mode fingerprints. The model provided a least root mean square error of cross validation (RMSECV) equal to an acrylamide concentration of 5.4 μg kg(-1) and standard error of prediction (SEP) of 14.8 μg kg(-1). The results obtained indicate that this strategy can be used to accurately predict the amounts of acrylamide formed during baking of biscuits. Such rapid estimation of acrylamide concentration can become a useful tool in evaluation of the effectivity of processes aiming at mitigation of this food processing contaminant. However, the robustness this approach with respect to variability in the chemical composition of ingredients used for preparation of biscuits should be tested further.

• Klíčová slova
• Acrylamide, Biscuits, Direct analysis in real time, Mass spectrometry, Multivariate regression analysis,
• MeSH
• akrylamid analýza   MeSH
• analýza hlavních komponent MeSH
• analýza potravin metody   MeSH
• chléb analýza   MeSH
• hmotnostní spektrometrie MeSH
• lineární modely MeSH
• metoda nejmenších čtverců MeSH
• multivariační analýza MeSH
• tandemová hmotnostní spektrometrie MeSH
• vaření * MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• Názvy látek
• akrylamid MeSH

Quantification models based on the processing of FTIR spectra by partial least squares regression (PLS) were created in order to develop a method for the determination of 2-ethylhexyl nitrate (2-EHN) in diesel fuels. The set of standards was prepared using 2-EHN, biodiesel (FAME) and various mineral diesel fuels (2-EHN free). The standards were prepared in the concentration range of 2-EHN of 0-2436mgkg-1. The set of the standards was divided into the calibration, validation and test sets. While the calibration set was used to build the model, validation set was used in order to optimize the model parameters. The test set of the standards was used to assess the predictive ability and repeatability of the model. Several hundreds of various models were developed and compared in order to find a suitable combination of the preprocessing methods and number of latent variables. The most promising model was developed using mean centered spectra in the form of their first derivative and smoothed using Gap-Segment derivative. The model showed quite good predictive ability and repeatability.

• Klíčová slova
• 2-EHN, 2-ethylhexyl nitrate, FTIR spectroscopy, Multivariate calibration, Partial least squares regression,
• MeSH
• benzin analýza   MeSH
• biopaliva analýza   MeSH
• dusičnany analýza   MeSH
• informatika * MeSH
• metoda nejmenších čtverců MeSH
• spektroskopie infračervená s Fourierovou transformací * MeSH
• Publikační typ
• časopisecké články MeSH
• Názvy látek
• 2-ethylhexyl nitrate MeSH Prohlížeč
• benzin MeSH
• biopaliva MeSH
• dusičnany MeSH