Catalytic and thermodynamic properties of glycosylated Bacillus cereus cyclodextrin glycosyltransferase.

Cyclodextrin glycosyltransferase (CGTase) was covalently coupled to five oxidized polysaccharides differing in structure and chemical nature. The conjugates were evaluated for the retained activity, kinetic and thermodynamic stability. The conjugated CGTase with oxidized dextran (MW 47000) had the highest retained specific activity (70.05%) and the highest half-life (T1/2) at 80°C. Compared to the native enzyme, the conjugated preparation exhibited higher optimum temperature, lower activation energy (Ea), lower deactivation constant rate (kd), higher T1/2, and higher D values (decimal reduction time) within the temperature range of 60-80°C. The values of thermodynamic parameters for irreversible inactivation of native and conjugated CGTase indicated that conjugation significantly decreased entropy (ΔS*) and enthalpy of deactivation (ΔH*). The results of thermodynamic analysis for cyclodextrin production from starch indicated that The enthalpy of activation (ΔH*) and free energy of activation (ΔG*), (free energy of transition state) ΔG*E-T and (free energy of substrate binding) ΔG*E-S values were lower for the conjugated CGTase. Similarly, there was significant impact on improvement of kcat, kcat/Km values. Both native and conjugated enzyme produce α-cyclodextrin from starch.

Slow modulations of high-frequency activity (40-140-Hz) discriminate preictal changes in human focal epilepsy.

Recent evidence suggests that some seizures are preceded by preictal changes that start from minutes to hours before an ictal event. Nevertheless an adequate statistical evaluation in a large database of continuous multiday recordings is still missing. Here, we investigated the existence of preictal changes in long-term intracranial recordings from 53 patients with intractable partial epilepsy (in total 531 days and 558 clinical seizures). We describe a measure of brain excitability based on the slow modulation of high-frequency gamma activities (40-140 Hz) in ensembles of intracranial contacts. In prospective tests, we found that this index identified preictal changes at levels above chance in 13.2% of the patients (7/53), suggesting that results may be significant for the whole group (p < 0.05). These results provide a demonstration that preictal states can be detected prospectively from EEG data. They advance understanding of the network dynamics leading to seizure and may help develop novel seizure prediction algorithms.