The Strength of Alpha Oscillations in the Electroencephalogram Differently Affects Algorithms Used for Anesthesia Monitoring.

BACKGROUND: Intraoperative patient monitoring using the electroencephalogram (EEG) can help to adequately adjust the anesthetic level. Therefore, the processed EEG (pEEG) provides the anesthesiologist with the estimated anesthesia level. The commonly used approaches track the changes from a fast- and a low-amplitude EEG during wakefulness to a slow- and a high-amplitude EEG under general anesthesia. However, besides these changes, another EEG feature, a strong oscillatory activity in the alpha band (8-12 Hz), develops in the frontal EEG. Strong alpha-band activity during general anesthesia seems to reflect an appropriate anesthetic level for certain anesthetics, but the way the common pEEG approaches react to changes in the alpha-band activity is not well explained. Hence, we investigated the impact of an artificial alpha-band modulation on pEEG approaches used in anesthesia research. METHODS: We performed our analyses based on 30 seconds of simulated sedation (n = 25) EEG, simulated anesthesia (n = 25) EEG, and EEG episodes from 20 patients extracted from a steady state that showed a clearly identifiable alpha peak in the density spectral array (DSA) and a state entropy (GE Healthcare) around 50, indicative of adequate anesthesia. From these traces, we isolated the alpha activity by band-pass filtering (8-12 Hz) and added this alpha activity to or subtracted it from the signals in a stepwise manner. For each of the original and modified signals, the following pEEG values were calculated: (1) spectral edge frequency (SEF95), (2) beta ratio, (3) spectral entropy (SpEntr), (4) approximate entropy (ApEn), and (5) permutation entropy (PeEn). RESULTS: The pEEG approaches showed different reactions to the alpha-band modification that depended on the data set and the amplification step. The beta ratio and PeEn decreased with increasing alpha activity for all data sets, indicating a deepening of anesthesia. The other pEEG approaches behaved nonuniformly. SEF95, SpEntr, and ApEn decreased with increasing alpha for the simulated anesthesia data (arousal) but decreased for simulated sedation. For the patient EEG, ApEn indicated an arousal, and SEF95 and SpEntr showed a nonuniform change. CONCLUSIONS: Changes in the alpha-band activity lead to different reactions for different pEEG approaches. Hence, the presence of strong oscillatory alpha activity that reflects an adequate level of anesthesia may be interpreted differently, by an either increasing (arousal) or decreasing (deepening) pEEG value. This could complicate anesthesia navigation and prevent the adjustment to an adequate, alpha-dominant anesthesia level, when titrating by the pEEG values.

Effect of Storage on Acrylamide and 5-hydroxymethylfurfural Contents in Selected Processed Plant Products with Long Shelf-life.

This study investigated the effects of storage and temperature duration on the stability of acrylamide (AA) and 5-hydroxymethylfurfural (HMF) in selected foods with long shelf-life. Products were analysed fresh and stored at temperatures of 4 and 25 °C after 6 and 12 months (with the exception of soft bread samples, which were analysed after 15 and 30 days). The AA and HMF contents were determined with RP-HPLC coupled to a diode array detector (DAD). AA and HMF were not stable in many processed plant products with a long shelf-life. The highest AA reduction and the largest increase in HMF content were observed in the samples stored at a higher temperature (25 °C) for 12 months. It was found that an initial water activity of 0.4 is favourable to HMF formation and that AA reduction may be considerably greater in stored products with a low initial water activity. The kind of product and its composition may also have a significant impact on acrylamide content in stored food. In the final period of storage at 25 °C, acrylamide content in 100% cocoa powder, instant baby foods, 20% cocoa powder and instant coffee was 51, 39, 35 and 33% lower than in products before storage, respectively. It was observed that a large quantity of ε-NH2 and SH groups of amino acids in some products can be assumed as the reason for the significant AA degradation.