Search results for "chemometrics"
showing 10 items of 101 documents
Complementary mobile-phase optimisation for resolution enhancement in high-performance liquid chromatography.
2000
An optimisation methodology in high-performance liquid chromatography (HPLC) is presented for the selection of two or more mobile phases having an optimal complementary resolution. The complementary mobile phases (CMPs) are selected in such a way that each one resolves optimally only some compounds in the mixture, while the remainder, resolved by the other mobile phase(s), can overlap among them. The methodology is based on the computation of a peak purity measurement for each solute, using an asymmetrical peak model for peak simulation. Two global resolution criteria (product of elementary resolutions and worst elementary resolution) and two methods for solving the problem (a systematic ex…
Multivariate data analysis of quality parameters in drinking water.
2001
The quality of water destined for human consumption has been treated as a multivariate property. Since most of the quality parameters are obtained by applying analytical methods, the routine analytical laboratory (responsible for the accuracy of analytical data) has been treated as a process system for water quality estimation. Multivariate tools, based on principal component analysis (PCA) and partial least squares (PLS) regression, are used in the present paper to: (i) study the main factors of the latent data structure and (ii) characterize the water samples and the analytical methods in terms of multivariate quality control (MQC). Such tools could warn of both possible health risks rela…
Feature selection strategies for quality screening of diesel samples by infrared spectrometry and linear discriminant analysis.
2012
Abstract A rapid approach has been developed for the characterization of diesel quality, based on attenuated total reflectance – Fourier transform infrared (ATR-FTIR) spectrometry, which could be useful for diagnosing the sample quality condition. As a supervised technique, linear discriminant analysis (LDA) was employed to process the spectrometric data. The role of variable selection methods was also evaluated. Successive projection algorithm (SPA) and genetic algorithm (GA) feature selection techniques were applied prior to the discriminative procedure. It was aimed to compare the effect of feature selection procedures on classification capability of IR spectrometry for the diesel sample…
Chromatographic multivariate quality control of pharmaceuticals giving strongly overlapped peaks based on the chromatogram profile
2004
In the present paper, the simultaneous quantification of two analytes showing strongly overlapped chromatographic peaks (alpha = 1.02), under the assumption that both available equipment and training of the laboratory staff are basic, is studied. A pharmaceutical preparation (Mutabase) containing two drugs of similar physicochemical properties (amitriptyline and perphenazine) is selected as case of study. The assays are carried out under realistic working conditions (i.e. routine testing laboratories). Uncertainty considerations are introduced in the study. A partial least squares model is directly applied to the chromatographic data (with no previous signal transformation) to perform quali…
Predicting antitrichomonal activity: A computational screening using atom-based bilinear indices and experimental proofs
2006
Existing Trichomonas vaginalis therapies are out of reach for most trichomoniasis people in developing countries and, where available, they are limited by their toxicity (mainly in pregnant women) and their cost. New antitrichomonal agents are needed to combat emerging metronidazole-resistant trichomoniasis and reduce the side effects associated with currently available drugs. Toward this end, atom-based bilinear indices, a new TOMOCOMD-CARDD molecular descriptor, and linear discriminant analysis (LDA) were used to discover novel, potent, and non-toxic lead trichomonacidal chemicals. Two discriminant functions were obtained with the use of non-stochastic and stochastic atom-type bilinear in…
Dragon method for finding novel tyrosinase inhibitors: Biosilico identification and experimental in vitro assays
2006
QSAR (quantitative structure-activity relationship) studies of tyrosinase inhibitors employing Dragon descriptors and linear discriminant analysis (LDA) are presented here. A data set of 653 compounds, 245 with tyrosinase inhibitory activity and 408 having other clinical uses were used. The active data set was processed by k-means cluster analysis in order to design training and prediction series. Seven LDA-based QSAR models were obtained. The discriminant functions applied showed a globally good classification of 99.79% for the best model Class=-96.067+1.988 x 10(2)X0Av +9 1.907 BIC3 + 6.853 CIC1 in the training set. External validation processes to assess the robustness and predictive pow…
Multi-target QSPR assemble of a Complex Network for the distribution of chemicals to biphasic systems and biological tissues
2008
Abstract Chemometrics, that based prediction on the probability of chemical distribution to different systems, is highly important for physicochemical, environmental, and life sciences. However, the amount of information is huge and difficult to analyze. A multi-system partition Complex Network (MSP-CN) may be very useful in this sense. We define MSP-CNs as large graphs composed by nodes (chemicals) interconnected by arcs if a pair of chemicals have similar partition in a given system. Experimental quantification of partition in many systems is expensive, so we can use a Quantitative Structure–Partition Relationship (QSPR) model. Unfortunately, with classic QSPR we need to use one model for…
New tyrosinase inhibitors selected by atomic linear indices-based classification models.
2005
In the present report, the use of the atom-based linear indices for finding functions that discriminate between the tyrosinase inhibitor compounds and inactive ones is presented. In this sense, discriminant models were applied and globally good classifications of 93.51% and 92.46% were observed for non-stochastic and stochastic linear indices best models, respectively, in the training set. The external prediction sets had accuracies of 91.67% and 89.44%. In addition, these fitted models were used in the screening of new cycloartane compounds isolated from herbal plants. A good behavior is shown between the theoretical and experimental results. These results provide a tool that can be used i…
Analysis of sterols by high-performance liquid chromatography/mass spectrometry combined with chemometrics
2006
A newly developed high-performance liquid chromatography/mass spectrometry (HPLC/MS) method has been successfully used to analyze plasma concentrations of various phytosterols (cholestanol and beta-sitosterol) and cholesterol metabolites (desmosterol and lathosterol). This was based on an unusual solvent combination of water/methanol vs. methanol/acetone/n-hexane applied on a Purospher Star RP-18e (125 x 2 mm, 3 microm) column, which proved excellent for the separation, identification and quantification of plasma sterols. Simple solid-phase extraction preparation of plasma samples was performed, followed by the developed fast and robust HPLC separation. Results on four groups of people were…
Rapid and Nondestructive Determination of Egg Freshness Category and Marked Date of Lay using Spectral Fingerprint
2020
The potential of nondestructive prediction of egg freshness based on near-infrared (NIR) spectra fingerprints would be beneficial to quality control officers and consumers alike. In this study, handheld NIR spectrometer in the range of 740 nm to 1070 nm and chemometrics were used to simultaneously determine egg freshness based on marked date of lay for eggs stored under cold and ambient conditions. The spectra acquired from the eggs were preprocessed using multiplicative scatter correction and principal component analysis (MSC-PCA). Linear discriminant analysis (LDA) was used to build identification model to predict the category of freshness, while partial least square regression (PLS-R) wa…