Peter Nemeček, Dáša Kružlicová and Lucia Remenárová
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
Jana Moravčíková, Ildikó Matušíková, Peter Nemeček, Alžbeta Blehová, Želmíra Balážová, Zdenka Gálová, Patrik Mészáros and Ján Kraic
Acceptance of genetically modified plants is restricted in EU by legislation, while the attitude of public is not favourable as well. Surveys show that knowledge about GM plants is getting increased. Newly developed strategies on GM safety for environment can be a crucial aspect for the (partial) acceptance in future. GM trees as non-edible plants might appear as more admissible, however, are relatively rarely discussed. We performed a comparative survey on knowledge and perception of GM forest trees among students at four Slovak universities. We also compared their responses between as well as with the outcome of similar cross-country survey in frames of the COST Action FP0905. The results point to very similar attitude of Slovak students when compared with students from other countries, no significant difference between responses of males and females, but also influence of age as well as orientation of their study (natural sciences vs. economy) on view of GM tree safety and placing on the market.
Katarína Vulganová, Tibor Maliar, Mária Maliarová, Peter Nemeček, Jana Viskupičová, Andrea Balážová and Jozef Sokol
Sage is medicinal plant, known for its antioxidant and anti-inflammatory effects. Eight extract samples were tested in this study: extract from Salvia officinalis L. varieties from two different geographical localities (Jaslovské Bohunice and Pobedim, Slovakia), Salvia officinalis L., variety “bicolor”, Salvia officinalis L., variety “purpurescens”, Salvia apiana, Salvia divinorum, and two callus cultures of Salvia sclarea L. and Salvia aethiopis L. The highest values for composite parameters were observed for extract from Salvia apiana. It can be concluded that prepared sage extract samples are rich on polyphenolic acids (2 950±265 μg.mL−1 GAeq.) and amines (197±5.50 μg.mL−1 TRPeq.). HPLC analysis confirmed the dominant content of rosmarinic acid in the extracts; the highest content was detected in the Salvia apiana extract (1 120±15 μg.mL−1). Extract from Salvia apiana expressed too the highest antioxidant activity (1 710 – 4 669 μg.mL−1TEAC). Similarly, the highest inhibition activity was observed for this extract on thrombin (57±3.3 %) and on other proteinases (over 80 %). Spearman correlation analysis and PCA analyses revealed a coherence between antioxidant activity of samples and their content of rosmarinic acid as well as inhibitory activity towards particular proteases, and revealed the significance of thiol based secondary metabolites. Cluster analysis demonstrates the differences of Salvia apiana extract from extracts of S. officinalis L., the group of S. divinorum extract and from callus cultures.