There have been published manuscripts which fully suggest that there may be a topographic variance of contact sensitivity in experimental animals such as guinea pigs, hamsters and mice, probably due to a large extent to the topographic difference of Langerhans cell population and to a little extent to impact on the induction site. This assay was done to establish the possibility of involvement of a certain topographic variance in contact sensitivity reaction. Three different anatomical sites were chosen for the induction in three groups of five guinea pigs: the conventional site of the nuchal region, and the sacral aod. ahdominal skin regions. For the elicitation, two different concentrations of DNCB were applied on three sites along both sides of the spine in the back. The contact sensitivity reaction elicited by DNCB in the group of the nuchal abdominal skin induction was definitely stronger at the site closer to the nuchal region than that found at sites closer to the sacral regior. but all animals of the group sensitized on the sacral region showed comparatively uniform reaction. Zvidently, contact sensitivity reaction is influenced mainly by topographic variance hut shows a litte difference depending upon induction sites.
Animals ; Cricetinae ; Dermatitis, Contact* ; Dinitrochlorobenzene ; Guinea Pigs* ; Guinea* ; Mice ; Sacrococcygeal Region ; Skin ; Spine

No abstract available.
Genetics* ; Hyperaldosteronism*

No abstract available.
Pulmonary Disease, Chronic Obstructive*

Sleep is an essential process maintaining the life cycle of the human. In parallel with physiological, cognitive, subjective, and behavioral changes that take place during the sleep, there are remarkable changes in the electroencephalogram (EEG) that reflect the underlying electro-physiological activity of the brain. However, analyzing EEG and relating the results to clinical observations is often very hard due to the complexity and a huge data amount. In this article, I introduce several linear and non-linear tools, developed to analyze a huge time series data in many scientific researches, and apply them to EEG to characterize various sleep states. In particular, the spectral analysis, detrended fluctuation analysis (DFA), and synchrony analysis are administered to EEG recorded during nocturnal polysomnography (NPSG) processes and daytime multiple sleep latency tests (MSLT). I report that 1) sleep stages could be differentiated by the spectral analysis and the DFA; 2) the gradual transition from Wake to Sleep during the sleep onset could be illustrated by the spectral analysis and the DFA; 3) electrophysiological properties of narcolepsy could be characterized by the DFA; 4) hypnic jerks (sleep starts) could be quantified by the synchrony analysis.
Brain ; Electroencephalography ; Humans ; Hypogonadism ; Life Cycle Stages ; Mitochondrial Diseases ; Narcolepsy ; Ophthalmoplegia ; Polysomnography ; Sleep Stages

No abstract available.
Diagnosis* ; Facial Nerve* ; Paralysis*

OBJECTIVE: Among various methods developed to quantitatively explore electroencephalograms (EEG), we focused on a wavelet method that was known to yield robust results under nonstationary conditions. The aim of this study was thus to introduce the wavelet method and demonstrate its potential use in clinical sleep studies. METHOD: This study involved artificial EEG specifically designed to validate the wavelet method. The method was performed to obtain time-dependent spectral power and phase angles of the signal. Synchrony of multichannel EEG was analyzed by an order parameter of the instantaneous phase. The standard methods, such as Fourier transformation and coherence, were also performed and compared with the wavelet method. The method was further validated with clinical EEG and ERP samples available as pilot studies at academic sleep centers. RESULT: The time-frequency plot and phase synchrony level obtained by the wavelet method clearly showed dynamic changes in the EEG waveforms artificially fabricated. When applied to clinical samples, the method successfully detected changes in spectral power across the sleep onset period and identified differences between the target and background ERP. CONCLUSION: Our results suggest that the wavelet method could be an alternative and/or complementary tool to the conventional Fourier method in quantifying and identifying EEG and ERP biomarkers robustly, especially when the signals were nonstationary in a short time scale (1-100 seconds).
Biomarkers ; Electroencephalography ; Fourier Analysis ; Pilot Projects

No abstract available.
Dermatitis, Atopic*

No abstract available.
Malaria*

No abstract available.
Thyroid Diseases* ; Thyroid Gland*

No abstract available.