A synthesis of licofelone using Fenton’s reagent

An efficient synthesis of licofelone, an anti-inflammatory drug currently undergoing phase-III clinical studies, based on Fenton-type radical alkylation of 2,3-dihydro-1H-pyrrolizine 3 with iodoacetonitrile or iodoacetates is reported. The iodoacetates can be replaced by NaI and by the corresponding bromoacetate.     

Multicomponent kinetic determinations using multivariate calibration techniques

Multivariate calibration techniques for use in multicomponent kinetic-based determinations are reviewed. Multivariate calibration is a chemometric tool that continues to grow in popularity among analytical chemists. Multicomponent kinetic methods depend on differences in rates of reactions or processes to distinguish among the components. Kinetic profiles or a combination of kinetic profiles and spectra are commonly used. Because of their ability to process large quantities of data, multivariate calibration techniques are well suited for kinetic-based determinations. The concepts and principles of multivariate calibration are discussed first. Classical least squares regression, principal component regression, partial least squares regression and artificial neural networks are the multivariate calibration techniques considered here in detail. Recent examples of the application of these techniques to multicomponent kinetic determinations are reviewed. Both single and multiwavelength kinetic data are considered.     

Improvement of multivariate calibration techniques applied to 1-to-N component mixtures through an optimized experimental design

This work describes a novel experimental design aimed at building a calibration set constituted by samples containing a different number of components. The algorithm performs a reiteration process to maintain the number of samples at the lower value as possible and to ensure an homogeneous presence of all the concentration levels. The mixture design was applied to a drug system composed by one-to-four components in different combination. The resolution of the system was performed by three multivariate UV spectrophotometric methods utilizing principal component regression (PCR) and partial last squares (PLS1 and PLS2) algorithms. The calibration set was composed by 61 references on four concentration levels, including 15 samples for each quaternary, ternary and binary composition and 16 one-component samples. The calibration models were optimized through a careful selection of number of factors and wavelength zones, in such a way as to remove interferences from instrumental noise and excipients present in the pharmaceutical formulations. The prediction power of the regression models were verified and compared by analysis of an external prediction set. The models were finally used to assay pharmaceutical specialities containing the studied drugs in one-to-four formulations.     

Direct synthesis of Stryker’s reagent from a Cu(II) salt

A convenient, one-pot procedure for the preparation of [(PPh₃)CuH]₆ from a Cu(II) precursor, Cu(OAc)₂ in the presence of organosilanes as the reducing agent is described. This method provides a simple route to Stryker’s reagent without the necessity of preparing and purifying reagents in additional steps.     

Interference modelling, experimental design and pre-concentration steps in validation of the Fenton's reagent for pesticides determination

The determination of atrazine in real samples (commercial pesticide preparations and water matrices) shows how the Fenton's reagent can be used with analytical purposes when kinetic methodology and multivariate calibration methods are applied. Also, binary mixtures of atrazine-alachlor and atrazine-bentazone in pesticide preparations have been resolved. The work shows the way in which interferences and the matrix effect can be modelled. Experimental design has been used to optimize experimental conditions, including the effect of solvent (methanol) used for extraction of atrazine from the sample. The determination of pesticides in commercial preparations was accomplished without any pre-treatment of sample apart from evaporation of solvent; the calibration model was developed for concentration ranges between 0.46 and 11.6 × 10⁻⁵ mol L⁻¹ with mean relative errors under 4%. Solid-phase extraction is used for pre-concentration of atrazine in water samples through C₁₈ disks, and the concentration range for determination was established between 4 and 115 μg L⁻¹approximately. Satisfactory results for recuperation of atrazine were always obtained.     

A high yielding, one-pot synthesis of dialkyl carbonates from alcohols using Mitsunobu’s reagent

A Mitsunobu-based protocol has been developed for the synthesis of symmetrical and unsymmetrical dialkylcarbonates from a variety of primary, secondary and tertiary alcohols using gaseous carbon dioxide, in good to excellent yields. This protocol is mild and efficient compared to other reported methods.     

An efficient, one-pot, synthesis of dithiocarbamates from the corresponding alcohols using Mitsunobu’s reagent

A Mitsunobu-based protocol has been developed for the synthesis of dithiocarbamates from the corresponding alcohols using carbon disulfide and amines in good to excellent yields. This protocol is mild, chemoselective and efficient compared to other reported methods.     

A high yielding, one-pot synthesis of O,S-dialkyl dithiocarbonates from alcohols using Mitsunobu’s reagent

A novel Mitsunobu-based protocol has been developed for the synthesis of O,S-dialkyl dithiocarbonates from a variety of primary, secondary and tertiary alcohols using carbon disulfide, in good to excellent yields. This protocol is mild and efficient compared to other reported methods.     

Regression models based on new local strategies for near infrared spectroscopic data

In this work, a comparative study of two novel algorithms to perform sample selection in local regression based on Partial Least Squares Regression (PLS) is presented. These methodologies were applied for Near Infrared Spectroscopy (NIRS) quantification of five major constituents in corn seeds and are compared and contrasted with global PLS calibrations. Validation results show a significant improvement in the prediction quality when local models implemented by the proposed algorithms are applied to large data bases.     

An assisted approach of the global optimization for the experimental conditions in capillary electrophoresis

Experimental conditions have effect on the separation of capillary electrophoresis (CE) directly. In this work, a set of index to describe the separation in CE was established properly. Based on a combination of genetic algorithm and least square support vector machine, an assisted approach of global optimization for experimental conditions was proposed for the first time, and it was applied to the separation of four synthetic compounds by CE in nonaqueous system. Under the optimum conditions obtained by this approach, the result of the experiment was satisfactory and proved that this novel approach was effective. Furthermore, we investigated the most important conditions that mainly affect the separation effectiveness of CE by partial least squares regression analysis. Because of the generalization of this new approach proposed, it can be applied to the optimization of other experimental processes.     

Combining synchronous fluorescence spectroscopy with multivariate methods for the analysis of petrol-kerosene mixtures

Synchronous fluorescence spectroscopy (SFS) is a rapid, sensitive and nondestructive method suitable for the analysis of multifluorophoric mixtures. The present study demonstrates the use of SFS and multivariate methods for the analysis of petroleum products which is a complex mixture of multiple fluorophores. Two multivariate techniques principal component regression (PCR) and partial least square regression (PLSR) have been successfully applied for the classification of petrol-kerosene mixtures. Calibration models were constructed using 35 samples and their validation was carried out with varying composition of petrol and kerosene in the calibration range. The results showed that the method could be used for the estimation of kerosene in kerosene-mixed petrol. The model was found to be sensitive, detecting even 1% contamination of kerosene in petrol.     

Simultaneous Kinetic‐Spectrophotometric Determination of Hydrazine and its Derivatives by Partial Least Squares and Principle Component Regression Methods

Simultaneous kinetic‐spectrophotometric determination of a ternary mixture of hydrazine (HZ) and its derivatives by principal component regression (PCR) and partial least squares (PLS) calibration is described. The methods were based on the difference observed in the reduction rate of iron(III) with HZ, thiosemicarbazide (TSCZ) and phenylhydrazine (PHZ) in the presence of 2,2′‐bipyridine (Bpy). The colored complex of [Fe(Bpy)₃]²⁺ was formed in sodium dodecyl sulfate (SDS) as micellar media, and then monitored at 520 nm. The results showed that simultaneous determination of HZ, TSCZ and PHZ could be performed in their concentration ranges of 1.0–70.0, 0.2–6.0 and 0.1–10.0 μg mL^?1, respectively. The root mean squares errors of prediction (RMSEP) of HZ, TSCZ and PHZ were 0.719, 0.164 and 0.105 (for PLS) 0.788, 0.166 and 0.993 (for PCR), respectively. Both methods (PCR and PLS) were validated using a set of synthetic sample mixtures and then applied for simultaneous determination of HZ, TSCZ and PHZ in water samples.     

Algorithms for multi‐group PLS

Several approaches of investigation of the relationships between two datasets where the individuals are structured into groups are discussed. These strategies fit within the framework of partial least squares (PLS) regression. Each strategy of analysis is introduced on the basis of a maximization criterion, which involves the covariances between components associated with the groups of individuals in each dataset. Thereafter, algorithms are proposed to solve these maximization problems. The strategies of analysis can be considered as extensions of multi‐group principal components analysis to the context of PLS regression. Copyright © 2014 John Wiley & Sons, Ltd.     

Rapid Mo(CO)6 catalysed one-pot deoxygenation of heterocyclic halo-benzyl alcohols with Lawesson’s reagent

A fast and efficient microwave promoted one-pot method for deoxygenation of heterocyclic halo-benzyl alcohols has been developed. The method does not cause dehalogenation of the substrates and provides the deoxygenated products in high yield after only 30 min.     

Modeling the performance of “up-flow anaerobic sludge blanket” reactor based wastewater treatment plant using linear and nonlinear approaches—A case study

The paper describes linear and nonlinear modeling of the wastewater data for the performance evaluation of an up-flow anaerobic sludge blanket (UASB) reactor based wastewater treatment plant (WWTP). Partial least squares regression (PLSR), multivariate polynomial regression (MPR) and artificial neural networks (ANNs) modeling methods were applied to predict the levels of biochemical oxygen demand (BOD) and chemical oxygen demand (COD) in the UASB reactor effluents using four input variables measured weekly in the influent wastewater during the peak (morning and evening) and non-peak (noon) hours over a period of 48 weeks. The performance of the models was assessed through the root mean squared error (RMSE), relative error of prediction in percentage (REP), the bias, the standard error of prediction (SEP), the coefficient of determination (R²), the Nash-Sutcliffe coefficient of efficiency (E_f), and the accuracy factor (A_f), computed from the measured and model predicted values of the dependent variables (BOD, COD) in the WWTP effluents. Goodness of the model fit to the data was also evaluated through the relationship between the residuals and the model predicted values of BOD and COD. Although, the model predicted values of BOD and COD by all the three modeling approaches (PLSR, MPR, ANN) were in good agreement with their respective measured values in the WWTP effluents, the nonlinear models (MPR, ANNs) performed relatively better than the linear ones. These models can be used as a tool for the performance evaluation of the WWTPs.     

Diagnostics of calibration methods: model adequacy of UV‐based determinations

Models such as ordinary least squares, independent component analysis, principle component analysis, partial least squares, and artificial neural networks can be found in the calibration literature. Linear or nonlinear methods can be used to explain the structure of the same phenomenon. Each type of model has its own advantages with respect to the other. These methods are usually grouped taxonomically, but different models can sometimes be applied to the same data set. Taxonomically, ordinary least square and artificial neural network use completely different analytical procedures but are occasionally applied to the same data set. The aim of the study of methodological superiority is to compare the residuals of models because the model with the minimum error is preferred in real analyses. Calibration models, in general, are based on deterministic and stochastic parts; in other words, the data are equal to the model + the error. Explaining a model solely using statistics such as the coefficient of determination or its related significance values is sometimes inadequate. The errors of a model, also called its residuals, must have minimum variance compared to its alternatives. Additionally, the residuals must be unpredictable, uncorrelated, and symmetric. Under these conditions, the model can be considered adequate. In this study, calibration methods were applied to the raw materials, hydrochlorothiazide and amiloride hydrochloride, of a drug, as well as a sample of the drug tablet. The applied chemical procedure was fast, simple, and reproducible. The various linear and nonlinear calibration methods mentioned above were applied, and the adequacy of the calibration methods was compared according to their residuals.     

Novel synthesis of oxa[9]helicenes by Lawesson’s reagent-mediated cyclization of helical quinone derivatives

New oxa[9]helicenes which possess one furan ring have been readily prepared by reactive helical quinone with Lawesson’s reagent or phosphorus pentasulfide in good yields. The versatility of this protocol has been demonstrated with various substituted helical quinones.     

A novel flow-based strategy for implementing differential kinetic analysis

Differential kinetic analysis can be implemented in a multi-pumping flow system, and this was demonstrated in relation to an improved spectrophotometric catalytic determination of iron and vanadium in Fe-V alloys. The method exploited the influence of Fe(II) and V(IV) on the rate of iodide oxidation by Cr(VI) under acidic conditions; therefore the Jones reductor was needed. The sample was inserted into an acidic KI stream that acted also as carrier stream, and a Cr(VI) solution was added by confluence. Successive measurements were performed during sample passage through the detector, each one related to a different yet reproducible condition for reaction development. Data treatment involved multivariate calibration by the PLS algorithm.The proposed system is very simple and rugged, allowing about 50 samples to be run per hour, meaning 48 mg KI per determination. The first two latent variables carry ca. 94% of the analytical information, pointing out that the intrinsic dimensionality of the data set is two. Results are in agreement with inductively coupled argon plasma-optical emission spectrometry.