The review will focus on the aspects of combinatorial chemistry and technologies that are more relevant in the modern pharmaceutical process. An historical, critical introduction is followed by three chapters, dealing with the use of combinatorial chemistry/high throughput synthesis in medicinal chemistry; the rational design of combinatorial libraries using computer-assisted combinatorial drug design; and the use of combinatorial technologies in biotechnology. The impact of “combinatorial thinking” in drug discovery in general, and in the examples reported in details, is critically discussed. Finally, an expert opinion on current and future trends in combinatorial chemistry and combinatorial technologies is provided.
The electrochemical behavior of an Fe(II)/Fe(III) redox couple in the presence of various selected amino acids has been studied using ferrocene-modified carbon paste electrode at pH = 7.4. Because of Fe(II)/Fe(III) solubility issues at physiological pH, ferrocene was used as a source of iron. Anodic oxidation of iron (pH = 7.2) occurred at 0.356 V and cathodic oxidation at 0.231 V, both vs Ag|AgCl. Treatment of the voltammetric data showed that it was a purely diffusion-controlled reaction with the involvement of one electron. After addition of amino acids, potential shifts and current changes can be observed on the voltammograms. Cyclic voltammetry experiments revealed the capability of amino acids to change the electrochemical behavior of the Fe(II)/Fe(III) redox couple.
The in vitro cell cultures of Vitis vinifera L. cv. St. Laurent were treated with two elicitors - synthetic methyl jasmonate and natural, prepared from grapevine plant infected with the Phaeomoniella chlamydospora, the agent causing the Esca disease of grapevine. Efficiency of phenolic compounds production after elicitation of cell culture was analysed immediately after treatment (15 min, 30 min, 60 min) and later (after 24, 48, and 72 hours). The cell growth and content of phenolic compounds (+)-catechin, (-)-epicatechin, p-coumaric acid, syringaldehyde, rutin, vanillic acid, and trans-resveratrol were analysed in cultivated cells as well as in cultivation medium. Pch-treatment increased production of total polyphenols the most significantly 15 min after the elicitation and in optimal time was 2.86 times higher than in nonelicited culture and 1.44 times higher than in MeJa induced cell culture.
The aim of this study was to determine the influence of malting on the antioxidant content in cereals such as wheat (PS Sunanka, Zaira, PS 57/11 and Vanda), oat (Dunajec) and barley (Laudis 550) harvested in 2013. Antioxidant and polyphenol contents of these cereals and malts were investigated. Secondary, technological parameters of prepared malts were evaluated and compared with malt from barley Laudis 550 used as reference material. Malting of selected cereals had an impact on antioxidant and polyphenol content and allowed a better extraction of these compounds from cereal matrix, except of barley malt, whose antioxidant and total polyphenol content remained comparable. For other cereal malts, antioxidant contents were 2.0, 1.8, 2.6, 2.9 and 3.2-fold higher and total polyphenol content were 1.8, 1.9, 1.9, 3.1 and 3.4-fold higher than in wheat (PS Sunanka, Zaira, PS 57/11, Vanda) and oat (Dunajec), respectively. From correlation analysis, the results showed that not all polyphenols released by malting have antioxidant activity. Technological parameters (friability, haze of wort, saccharification rate, filtration rate, extract and diastatic power) also indicated that good malt quality had oat Dunajec and wheat PS Sunanka and Zaira in comparison with reference material (barley Laudis 550).
One of the most essential parameters limiting the potential use of the ecosystem (soil, water) is the content of the organic matter. The natural organic matter (NOM) is a ubiquitous component of the lithosphere and hydrosphere that constitutes one of the largest reservoirs of the carbon in the environment. Natural organic substances play several important functions in ecosystems and they are necessary for their normal functioning. Despite many years of the research and using many advanced analytical techniques, their structure has not been fully explained. The main aim of this review is to present the actual state of the knowledge about the natural organic matter and provide a comprehensive overview of the research that has explored up to date in this matter. The additional attention was focused on the relations within and between humic and fulvic acids in terrestrial and aquatic environments. Special attention is focused on the analytical methods used to analysis natural organic matter
The determination of the sensorial quality of wines is of great interest for wine consumers and producers since it declares the quality in most of the cases. The sensorial assays carried out by a group of experts are time-consuming and expensive especially when dealing with large batches of wines. Therefore, an attempt was made to assess the possibility of estimating the wine sensorial quality with using routinely measured chemical descriptors as predictors. For this purpose, 131 Slovenian red wine samples of different varieties and years of production were analysed and correlation and principal component analysis were applied to find inter-relations between the studied oenological descriptors. The method of artificial neural networks (ANNs) was utilised as the prediction tool for estimating overall sensorial quality of red wines. Each model was rigorously validated and sensitivity analysis was applied as a method for selecting the most important predictors. Consequently, acceptable results were obtained, when data representing only one year of production were included in the analysis. In this case, the coefficient of determination (R2) associated with training data was 0.95 and that for validation data was 0.90. When estimating sensorial quality in categorical form, 94 % and 85 % of correctly classified samples were achieved for training and validation subset, respectively.
This paper evaluates the effect of simulated conditions of artificial aging on sorption capacity of two types of biochar. These were produced by slow pyrolysis from different feedstock - beech wood chips (BC A) and garden green waste residues (BC B). Cadmium served as a model for potentially toxic metals. Twenty freeze-thaw cycles were used to simulate physical aging. The determination of biochar physicochemical properties showed main changes in CEC and SA values of aged sorbents. The maximum sorption capacities of aged BC A sorbent were higher by about 26 % and aged BC B sorbent by about 20% compared to Qmax of non-aged biochar. Qmax of aged BC B peaked at 9.4 mg g-1 whereas BC A sorbed significantly less Cd. FT-IR analyses confirmed the changes in structural composition and content of functional groups on biochar surfaces. The artificial physical aging model was assessed as an efficient tool for investigation of natural weathering conditions.
Reactive forms of cerium oxide were prepared by a thermal decomposition of various precursors, namely carbonates, oxalates and citrates, commercially available nanocrystalline cerium oxide (nanoceria) was involved in the study for comparison. Scanning electron microscopy (SEM) and x-ray diffraction analysis (XRD) were used to examine the morphology and crystallinity of the samples, respectively, whereas the Brunauer-Emmett-Teller (BET) method of nitrogen adsorption was used to determine surface areas. Interactions of cerium oxide with some phosphorus-containing compounds were investigated. Some of the examined samples, especially those prepared by annealing from carbonate precursors, exhibited an outstanding ability to destroy highly toxic organophosphates, such as pesticides (parathion methyl), or nerve agents (soman, VX). There were identified some relations between the degradation efficiency of cerium oxides and their crystallinity. It was also shown that cerium oxide is able to destroy one of widely used flame retardants - triphenyl phosphate. A phosphatase-mimetic activity of various cerium oxides was examined with the aid of a standardized phosphatase test.
Improving the micronutrients in food has become an important field of the Second Green Revolution. In recent years, minor bioactive compounds such as polyphenols, pigments and carotenoids, have attracted more and more interest from both researchers and food manufactures as health-promoting and disease-preventing effects in both in vitro and in vivo studies. One of plant pigments, wheat anthocyanins as plant phenolics are increasingly attractive as natural compounds positively affecting consumer´s health and condition moreover wheat is staple food source consumed usually daily. For a purple, blue, or red colour of wheat seed are responsible glycosylated cyanidins, delphinidins, malvinidins, pelargonidins, petunidins, and peonidins located in aleurone layer or pericarp, respectively. Other than white seed colour is not natural for common hexaploid wheat but this trait can be introduced from donors by aimed breeding programs. The way of wheat anthocyanins to provide positive effects for consumer´s physiology is limited due to their specific occurrence in seed parts usually removed during grain milling practice and lower stability during processing to foods
Discharge of heavy metals into aquatic ecosystems has become a matter of concern over the last few decades. The search for new technologies involving the removal of toxic metals from wastewaters has directed the attention to biosorption, based on metal binding capacities of various biological materials. Degree of sorbent affinity for the sorbate determines its distribution between the solid and liquid phases and this behavior can be described by adsorption isotherm models (Freundlich and Langmuir isotherm models) representing the classical approach. In this study, an artificial neural network (ANN) was proposed to predict the sorption efficiency in single and binary component solutions of Cd2+, Zn2+ and Co2+ ions by biosorbent prepared from biomass of moss Rhytidiadelphus squarrosus. Calculated non-linear ANN models presented in this paper are advantageous for its capability of successful prediction, which can be problematic in the case of classical isotherm approach. Quality of prediction was proved by strong agreement between calculated and measured data, expressed by the coefficient of determination in both, single and binary metal systems (R2= 0.996 and R2= 0.987, respectively). Another important benefit of these models is necessity of significantly smaller amount of data (about 50%) for the model calculation. Also, it is possible to calculate Qeq for all studied metals by one combined ANN model, which totally overcomes a classical isotherm approach