Relationship between frequency spectrum of heart rate variability and autonomic nervous activities during sleep in newborns.

INTRODUCTION: We analyzed the frequency spectrum of two neonatal sleep stages, namely active sleep and quiet sleep, and the relationship between these sleep stages and autonomic nervous activity in 74 newborns and 16 adults as a comparison. METHOD: Active and quiet sleep were differentiated by electroencephalogram (EEG) patterns, eye movements, and respiratory wave patterns; autonomic activity was analyzed using the RR interval of simultaneously recorded electrocardiogram (ECG) signals. Power values (LFa, absolute low frequency; HFa, absolute high frequency), LFa/HFa ratio, and the values of LFn (normalized low frequency) and HFn (normalized high frequency) were obtained. Synchronicity between the power value of HFa and the LFa/HFa ratio during active and quiet sleep was also examined by a new method of chronological demonstration of the power values of HFa and LFa/HFa. RESULTS: We found that LFa, HFa and the LFa/HFa ratio during active sleep were significantly higher than those during quiet sleep in newborns; in adults, on the other hand, the LFa/HFa ratio during rapid eye movement (REM) sleep, considered as active sleep, was significantly higher than that during non-REM sleep, considered as quiet sleep, and HFa values during REM sleep were significantly lower than those during non-REM sleep. LFn during quiet sleep in newborns was significantly lower than that during active sleep. Conversely, HFn during quiet sleep was significantly higher than that during active sleep. Analysis of the four classes of gestational age groups at birth indicated that autonomic nervous activity in a few preterm newborns did not reach the level seen in full-term newborns. Furthermore, the power value of HFa and the LFa/HFa ratio exhibited reverse synchronicity. CONCLUSION: These results indicate that the autonomic patterns in active and quiet sleep of newborns are different from those in REM and non-REM sleep of adults and may be develop to the autonomic patterns in adults, and that parasympathetic activity is dominant during quiet sleep as compared to active sleep from the results of LFn and HFn in newborns. In addition, in some preterm infants, delayed development of the autonomic nervous system can be determined by classifying the autonomic nervous activity pattern of sleep stages.

Phototherapy with blue and green mixed-light is as effective against unconjugated jaundice as blue light and reduces oxidative stress in the Gunn rat model.

OBJECTIVE: Phototherapy using blue light-emitting diodes (LED) is effective against neonatal jaundice. However, green light phototherapy also reduces unconjugated jaundice. We aimed to determine whether mixed blue and green light can relieve jaundice with minimal oxidative stress as effectively as either blue or green light alone in a rat model. METHODS: Gunn rats were exposed to phototherapy with blue (420-520 nm), filtered blue (FB; 440-520 nm without<440-nm wavelengths, FB50 (half the irradiance of filtered blue), mixed (filtered 50% blue and 50% green), and green (490-590 nm) LED irradiation for 24h. The effects of phototherapy are expressed as ratios of serum total (TB) and unbound (UB) bilirubin before and after exposure to each LED. Urinary 8-hydroxy-2'-deoxyguanosine (8-OHdG) was measured by HPLC before and after exposure to each LED to determine photo-oxidative stress. RESULTS: Values < 1.00 indicate effective phototherapy. The ratios of TB and UB were decreased to 0.85, 0.89, 1.07, 0.90, and 1.04, and 0.85, 0.94, 0.93, 0.89, and 1.09 after exposure to blue, filtered blue, FB50, and filtered blue mixed with green LED, respectively. In contrast, urinary 8-OHdG increased to 2.03, 1.25, 0.96, 1.36, 1.31, and 1.23 after exposure to blue, filtered blue, FB50, mixed, green LED, and control, indicating side-effects (> 1.00), respectively. CONCLUSIONS: Blue plus green phototherapy is as effective as blue phototherapy and it attenuates irradiation-induced oxidative stress. PRACTICE IMPLICATIONS: Combined blue and green spectra might be effective against neonatal hyperbilirubinemia.

[An attempt to classify patients with dementia by detrended fluctuation analysis of electroencephalographic data --a preliminary study].

We investigated changes of the scaling exponent alpha estimated by detrended fluctuation analysis (DFA) of electroencephalograms (EEG) in patients with dementia including Alzheimer's disease(AD), and attempted to apply a method of pattern recognition using the alpha value-based feature vector to classify dementia. In 9 patients with AD, 8 patients with other types of dementia (vD), and 7 patients without dementia(C), DFA was performed for approximately one minute with background EEG data recorded at 16 different scalp monopoles. The alpha values were significantly higher in patients with AD at electrodes F7, C3, P3, P4, T3, and T5 than in patients without dementia. No significant difference in alpha values was found between patients with vD and without dementia. Then, an artificial neural network (ANN) was trained on the alpha value-based feature vector of EEG to classify patients with dementia into AD and vD. The trained ANN successfully diagnosed all four new test cases of AD. From these observations, it is suggested that AD has a specific pattern in the alpha value-based feature vector. Thus, pattern recognition using alpha value-based feature vector may be useful for the classification of dementia.