N-Acyl-α-amino acids were efficiently transformed in a two-step procedure into 1-N-(acylamino)alkyltriphenylphosphonium salts, new powerful α-amidoalkylating agents. The effect of the α-amino acid structure, the base used [MeONa or a silica gel-supported piperidine (SiO(2)-Pip)], and the main electrolysis parameters (current density, charge consumption) on the yield and selectivity of the electrochemical decarboxylative α-methoxylation of N-acyl-α-amino acids (Hofer-Moest reaction) was investigated. For most proteinogenic and all studied unproteinogenic α-amino acids, very good results were obtained using a substoichiometric amount of SiO(2)-Pip as the base. Only in the cases of N-acylated cysteine, methionine, and tryptophan, attempts to carry out the Hofer-Moest reaction in the applied conditions failed, probably because of the susceptibility of these α-amino acids to an electrochemical oxidation on the side chain. The methoxy group of N-(1-methoxyalkyl)amides was effectively displaced with the triphenylphosphonium group by dissolving an equimolar amount of N-(1-methoxyalkyl)amide and triphenylphosphonium tetrafluoroborate in CH(2)Cl(2) at room temperature for 30 min, followed by the precipitation of 1-N-(acylamino)alkyltriphenylphosphonium salt with Et(2)O.

One of the aspects of ammonia toxicity to brain cells is increased production of nitric oxide (NO) by NO synthases (NOSs). Previously we showed that ammonia increases arginine (Arg) uptake in cultured rat cortical astrocytes specifically via y + L amino acid transport system, by activation of its member, a heteromeric y + LAT2 transporter. Here, we tested

Component analysis is one of the most important methods used for electroencephalographic (EEG) signal decomposition, and the so-called independent component analysis (ICA) is commonly used. The main function of the ICA algorithm is to find a linear representation of non-Gaussian data whose elements are statistically independent or at least as independent as possible. There are many commercial solutions for EEG signal acquisition. Usually, together with the EEG, one gets a dedicated software to handle the signal. However, quite often, the software does not provide researchers with all necessary functions. A high-performance, dense-array EGI-EEG system is distributed with the NetStation software. Although NetStation is a powerful tool, it does not have any implementation of the ICA algorithm. This causes many problems for researchers who want to export raw data from the amplifier and then work on it using some other tools such as EEGLAB for MATLAB, as these data are not fully compatible with the EGI format. We will present the C++ implementation of ICA that can handle filtered data from the EGI with better affordability. Our tool offers visualization of raw signal and ICA algorithm results and will be distributed under Freeware license.

Despite the quick development of medicine and associated medical technology, there are still many patients with very severe neurological deficits who need far more sophisticated solutions, such as brain computer interfaces (BCIs). Our research aims at becoming familiar with BCI technology and the assessment of the possibilities of selected subjects in the area of P300-based BCI. An indirect aim is a discussion on the procedures of patient preparation for BCI installation, possible threats and limitations. Our research presents one of the possible efforts towards better documentation of investigating neural correlates of brain processing.