Encapsulation of Metronidazole in Biocompatible Macrocycles and Structural Characterization of Its Nano Spray-Dried Nanostructured Composite

Due to the great potential of biocompatible cucurbit[7]uril (CB7) and 4-sulfonatocalix[4]arene (SCX4) macrocycles in drug delivery, the confinement of the pharmaceutically important metronidazole as an ionizable model drug has been systematically studied in these cavitands. Absorption and fluorescence spectroscopic measurements gave 1.9 × 10⁵ M⁻¹ and 1.0 × 10⁴ M⁻¹ as the association constants of the protonated metronidazole inclusion in CB7 and SCX4, whereas the unprotonated guests had values more than one order of magnitude lower, respectively. The preferential binding of the protonated metronidazole resulted in 1.91 pH unit pK_a diminution upon encapsulation in CB7, but the complexation with SCX4 led to a pK_a decrease of only 0.82 pH unit. The produced protonated metronidazole–SCX4 complex induced nanoparticle formation with protonated chitosan by supramolecular crosslinking of the polysaccharide chains. The properties of the aqueous nanoparticle solutions and the micron-sized solid composite produced therefrom by nano spray drying were unraveled. The results of the present work may find application in the rational design of tailor-made self-assembled drug carrier systems.     

Stereoselective Direct N-Trifluoropropenylation of Heterocycles with a Hypervalent Iodonium Reagent

The availability and synthesis of fluorinated enamine derivatives such as N-(3,3,3-trifluoropropenyl)heterocycles are challenging, especially through direct functionalization of the heterocyclic scaffold. Herein, a stereoselective N-trifluoropropenylation method based on the use of a bench-stable trifluoropropenyl iodonium salt is described. This reagent enables the straightforward trifluoropropenylation of various N-heterocycles under mild reaction conditions, providing trifluoromethyl enamine type moieties with high stereoselectivity and efficiency.     

Non-invasive PGAA,PIXE and ToF-ND analyses on Hungarian Bronze Age defensive armour

Non-invasive, archaeometric analyses on selected Hungarian Bronze Age defensive armour is presented here: three greaves, three helmets two shields as well as one vessel fragment were analysed with PIXE, PGAA and TOF-ND. The detected alloy elemental and phase composition as well as its intergranular or spatial concentration distribution reveals important insights into the alloys used and the manufacturing techniques applied c. 1200–950 BC, and allows to reconstruct the production techniques used during the Late Bronze Age.     

New fluorescent isoquinoline derivatives

Various structural modifications of 3-amino and 3-hydroxyisoquinolines have been carried out to provide new fluorescent derivatives. The transformations involved nucleophilic substitution of a bromine atom or a triflate moiety at positions 1 and 3, respectively, as well as the condensation reaction of a 3-amino group with triethyl orthoformate and subsequent transformation with amines to give amidines. The new compounds have been studied by fluorescence spectroscopy.     

Mucin-electrolyte interactions at the solid-liquid interface probed by QCM-D

The interaction between mucin and ions has been investigated by employing the quartz crystal microbalance technique with measurement of energy dissipation. The study was partially aimed at understanding the adsorption of mucin on surfaces with different chemistry, and for this purpose, surfaces exposing COOH, OH, and CH(3) groups were prepared. Mucin adsorbed to all three types of functionalized gold surfaces. Adsorption to the hydrophobic surface and to the charged hydrophilic surface (COOH) occured with high affinity despite the fact that in the latter case both mucin and the surface were negatively charged. On the uncharged hydrophilic surface exposing OH groups, the adsorption of mucin was very low. Another aim was to elucidate conformational changes induced by electrolytes on mucin layers adsorbed on hydrophobic surfaces from 30 mM NaNO(3). To this end, we investigated the effect of three electrolytes with increasing cation valance: NaCl, CaCl(2) and LaCl(3). At low NaCl concentrations, the preadsorbed layer expands, whereas at higher concentrations of NaCl the layer becomes more compact. This swelling/compacting of the mucin layer is fully reversible for NaCl. When the mucin layer instead is exposed to CaCl(2) or LaCl(3), compaction is observed at 1 mM. For CaCl(2), this process is only partially reversible, and for LaCl(3), the changes are irreversible within the time frame of the experiment. Finally, mucin interaction with the DTAB cationic surfactant in an aqueous solution of different electrolytes was evaluated with turbidimetry measurements. It is concluded that the electrolytes used in this work screen the association between mucin and DTAB and that the effect increases with increasing cation valency.     

Use of supercritical CO2‐aided and conventional melt extrusion for enhancing the dissolution rate of an active pharmaceutical ingredient

Dispersing at the molecular level a drug in a polymer matrix is a major challenge to be addressed by the pharmaceutical industry to enhance its bioavailability or to control its release. Melt extrusion and supercritical CO₂‐aided melt extrusion of solid pharmaceutical formulations were performed to enhance the dissolution rate of carvedilol, taken as a model of poorly soluble drug. The presence of the drug improved the processability of the polyacrylate matrix (Eudragit E) through its plasticizing effect. The supercritical method was found gentle compared with melt extrusion owing to the shorter residence time and lower processing temperature and melt viscosity. No traces of decomposition of the drug could be detected after the supercritical extrusion process based on capillary electrophoresis results. This extrusion process resulted in effective homogenization of the components and amorphization of the drug according to Raman mapping, Fourier transform infrared spectrometry, X‐ray diffraction, and polarized light microscopy. The kinetics of dissolution can be dramatically improved. Copyright © 2011 John Wiley & Sons, Ltd.     

Selective Acceleration of the Protonated Merocyanine‐Spiropyran Photochromic Transformation by Inclusion in Cucurbit[7]uril

The effect of cucurbit[7]uril (CB7) on the spiropyran‐merocyanine photochromic interconversion was studied in acidic and alkaline aqueous solutions. The merocyanine (MC) isomer was found to be the thermodynamically most stable form both in water and in the presence of CB7. A preferential binding of the protonated merocyanine (MCH⁺) to CB7 was observed with an equilibrium constant of 7.4 × 10⁴ m ^?1, and the complex formation led to significant diminution of acidity of the guest. The photoinduced transformation of MCH⁺ to the spiropyran isomer was accelerated 2.3‐fold upon addition of CB7, whereas the rates of the other photochromic processes were not affected. The partial inclusion of MCH⁺ in CB7 led to dual fluorescence due to the incomplete deprotonation in the singlet‐excited state.     

Comparison of chemometric methods in the analysis of pharmaceuticals with hyperspectral Raman imaging

Chemical imaging method of vibrational spectroscopy, which provides both spectral and spatial information, creates a three‐dimensional (3D) dataset with a huge amount of data. When the components of the sample are unknown or their reference spectra are not available, the classical least squares (CLS) method cannot be applied to create visualized distribution maps. Raman image datasets can be evaluated even in such cases using multivariate (chemometric) methods for extracting the needed hidden information. The capability of chemometrics‐assisted Raman mapping is evaluated through the analysis of pharmaceutical tablets (considered as unknown) with the aim of estimating the pure component spectra based on the collected Raman image. Six chemometric methods, namely, principal component analysis (PCA), maximum autocorrelation factors (MAF), sample–sample 2D correlation spectroscopy (SS2D), self‐modeling mixture analysis (SMMA), multivariate curve resolution–alternating least squares (MCR‐ALS), and positive matrix factorization (PMF), were compared. SMMA was found to be the best choice to determine the number of components. MCR‐ALS and PMF provided the pure component spectra with the highest quality. MCR‐ALS was found to be superior to PMF in the estimation of Raman scores (which correspond to the concentrations) and yielded almost the same results as CLS (using the real reference spectra). Thus, the combination of Raman mapping and chemometrics could be successfully used to characterize unknown pharmaceuticals, identify their ingredients, and obtain information about their structures. This may be useful in the struggles against illegal and counterfeit products and also in the field of pharmaceutical industry when contaminants are to be identified. Copyright © 2011 John Wiley & Sons, Ltd.     

Comparison of multivariate linear regression methods in micro‐Raman spectrometric quantitative characterization

Chemical imaging was used in this study as a powerful analytical tool to characterize pharmaceuticals in solid form. The majority of analyses are evaluated with bilinear modelling using only the pure component spectra or just the chemical images themselves to estimate the concentrations in each pixel, which are far from true quantitative determination. Our aim was to create more accurate concentration images using regression methods. For the first time in chemical imaging, variable selections with interval partial least squares (PLS) and with genetic algorithms (PLS‐GA) were applied to increase the efficiency of the models. These were compared to numerous bilinear modelling and multivariate linear regression methods such as univariate regression, classical least squares (CLS), multivariate curve resolution–alternating least squares (MCR‐ALS), principal component regression (PCR) and partial least squares (PLS). Two component spray‐dried pharmaceuticals were used as a model. The paper is shown that, in contrast to the usual way of using either external validation or cross‐validation, both should be performed simultaneously in order to get a clear picture of the prediction errors and to be able to select the appropriate models. Using PLS with variable selection, the root mean square errors were reduced to 3% per pixel by keeping only those peaks that are truly necessary for the estimation of concentrations. It is also shown that interval PLS can point out the best peak for univariate regression, and can thereby be of great help even when regulations allow only univariate models for product quality testing. Variable selection, besides yielding more accurate overall concentrations across a Raman map, also reduces the deviation among pixel concentrations within the images, thereby increasing the sensitivity of homogeneity studies. Copyright © 2015 John Wiley & Sons, Ltd.