Unique demographic situation in the United Arab Emirates

A method which optimizes on global properties of sample recordings is proposed for the definition of and the discrimination between electroencephalogram (EEG) classes. The sample was drawn from students at the University of Heidelberg from 1974 to 1978 and consists of 15 healthy index cases clinically ascertained as belonging to the low voltage EEG group. In addition, the three clinically defined groups: diffuse β (18 index cases), borderline α (12 index cases) and monomorphous α (18 index cases) have been included in the study, as well as the first degree relatives of the index cases, thus providing a clinical classification into four groups. The proposed method provides an automatic and reliable classification algorithm using discriminant and cluster analysis. The relation between such an automatized classification and clinical classification schemes is investigated. In particular, the inheritance of the low voltage, EEG, the question on sex differences and the question of a simple Mendelian mechanism had been examined. The method of random splittings had been applied for discriminant and cluster analysis. Our findings can be summarized as follows: (1) except for the monomorphous α EEG group, the clinical classification shows rather marginal separation (discriminating performance 60% to 75%), while a new and more reliable grouping scheme improves the discriminating performance up to 87% to 91%. The latter scheme leads to the concept of personal channel pattern (PCP) and was compared to the clinical classification scheme by means of contingency tables; (2) only a weak correlation between the clinically and PCP-based groups could be found (Cramér Index: 0.27). Accordingly, we continued to investigate the extent to which the proposed EEG classification scheme can nevertheless explain the genetic mechanisms apparently involved in the low voltage EEG. We thus considered the role of sex differences manifest in our proposed new grouping scheme; (3) males occurred more frequently in the new group 3 and females more frequently in the new group 1. In this regard, a much better correlation of the new groups between mothers and children than between fathers and children was observed; and (4) with help of our new PCP scheme, we have been able to reproduce a simple two gene Mendelian scheme to explain inheritance of the clinical low voltage EEG group. In this PCP-based scheme, the low voltage property does not occur when dominance of a certain gene (called gene A) is absent. © 1996 Wiley-Liss, Inc.     

Selecting relevant electrode positions for classification tasks based on the electro-encephalogram

The aim is to describe a general approach to determining important electrode positions when measured electro-encephalogram signals are used for classification. The approach is exemplified in the frame of the brain-computer interface, which crucially depends on the classification of different brain states. To classify two brain states, e.g. planning of movement of right and left index fingers, three different approaches are compared: classification using a physiologically motivated set of four electrodes, a set determined by principal component analysis and electrodes determined by spatial pattern analysis. Spatial pattern analysis enhances the classification rate significantly from 61.3±1.8% (with four electrodes) to 71.8±1.4%, whereas the classification rate using principal component analysis is significantly lower (65.2±1.4%). Most of the 61 electrodes used have no influence on the classification rate, so that, in future experiments, the setup can be simplified drastically to six to eight electrodes without loss of information.     

An improved technique for monitoring the drinking behavior of mice

A set of calibrated lickometers provides continuous, quantitative monitoring of fluid consumption. It has been used in our laboratory at four levels of temporal resolution: 24 hr, 1 hr, 6 min, and for counting of individual licks. Convenient features are mounting of the licking tube-bottle assembly on the cage top (which permits the use of disposable plastic cages with litter) and automated collection of data with microcomputers.     

分子构效关系研究的模式识别方法

定量构效关系 QSAR是研究并揭示物质结构和活性之间的联系 ,近年来有广泛的研究与应用。在一定程度上 ,联系揭示的是一种模式识别的问题 ,本文介绍了在此类研究中所涉及到的模式识别方法 ,并作了一些前景展望     

Carbohydrate expression profile of colorectal cancer cells is relevant to metastatic pattern and prognosis

Carbohydrate expression of cancer cells is closely related to the metastatic nature of colorectal cancer. In the present study we investigated the relevance of carbohydrate expression profiles of colorectal cancer cells in the primary lesion to metastatic distribution patterns as well as prognosis in 134 cases. Carbohydrate expression was estimated by histochemistry with 17 kinds of lectins and 3 kinds of Lewis-related monoclonal antibodies (MAbs), and correlations between the staining and clinicopathological parameters were examined. The results showed that lymphatic invasion, lymph node metastasis, and peritoneal metastasis correlated with staining with lectins that bind galactose/N-acetylgalactosamine residues (Gal/GalNAc) such as Maclura pomifera (MPA), Arachis hypogaea (PNA), Helix pomatia (HPA), and Vicia villosa (VVA). In contrast, hepatic metastasis correlated with staining with Anguilla anguilla lectin (AAA), anti-Lewis^X (LEX-2), anti-sialyl Lewis^a (NS19-9), and anti-sialyl-dimeric Lewis^X (FH-6) MAbs, all of which bind preferentially to fucosylated carbohydrate chains. The five-year survival rate of patients was related to the staining of cancers with MPA, HPA, FH-6 or NS19-9, and MPA- and FH-6 staining were independent prognostic factors. We conclude that carbohydrate expression profiles of cancer cells are relevant to the route of tumor cell dissemination, metastatic pattern as well as prognosis of colorectal cancer.     

DNA polymorphism among isolates from multiple sites of a patient with chronic herpes simplex virus, type 1 infection

DNA polymorphisms among independent isolates of herpes simplex virus (HSV) type 1 were studied from a 7-year-old male patient with recurrent infections of the skin and internal organs. In the patient's serum, HSV antibodies could not be detected by complement fixation, enzyme-linked immunosorbent assay (ELISA), or neutralization tests. ELISA tests for the presence of antibodies to human immunodeficiency virus were also negative. One HSV isolate was obtained from mesenteric nodes biopsied in 1983; one from skin in 1984; and three (postmortem) from brain, lungs, and liver in 1985. Restriction enzymes Eco RI, Bgl II, Hind III, Kpn I, and Bam H1 digestion patterns of the five isolates were similar. However, Sal I digests of isolates from skin, mesenteric nodes, lungs, and liver showed variations that were distinct from that of the brain isolate. Although Sal I digests of skin, mesenteric nodes, lungs, and liver isolates share a common variation in lacking F and G, the liver isolate can be further differentiated because of the gain of a restriction site on the H fragment. Thus, the three distinct variants observed were the isolates from brain (variant 1); from skin, mesenteric nodes, and lungs (variant 2); and from liver (variant 3). The fragments involved in variations among these isolates (presence or absence of Sal, G and H) are from the unique short and long regions (invariable regions) of the genome and therefore do not show heterogeneity in size. The extent of variation among these isolates is less than that seen among epidemiologically unrelated strains, suggesting that they originated from a single infecting strain, probably the brain isolate.     

Training to yoga respiration selectively increases respiratory sensation in healthy man

Because yoga practitioners think they are benefiting from their breath training we hypothesized that yoga respiration training (YRT) could modify the respiratory sensation. Yoga respiration (YR) ("ujjai") consisted of very slow, deep breaths (2-3 min(-1)) with sustained breath-hold after each inspiration and expiration. At inclusion in the study and after a 2-month YRT program, we determined in healthy subjects their eupneic ventilatory pattern and their capacity to discriminate external inspiratory resistive loads (respiratory sensation), digital tactile mechanical pressures (somesthetic sensation) and sound-pressure stimulations (auditory sensation). Data were compared to a gender-, age-, and weight-matched control group of healthy subjects who did not undergo the YRT program but were explored at the same epochs. After the 2-month YRT program, the respiratory sensation increased. Thus, both the exponent of the Steven's power law (Psi=kPhin) and the slope of the linear-linear plot between Psi and mouth pressure (Pm) were significantly higher, and the intercept with ordinate axis of the Psi versus Pm relationship was lower. After YRT, the peak Pm developed against inspiratory loads was significantly lower, reducing the load-induced activation of respiratory afferents. YRT induced long-lasting modifications of the ventilatory pattern with a significant lengthening of expiratory duration and a modest tidal volume increase. No significant changes in somesthetic and auditory sensations were noted. In the control group, the respiratory sensation was not modified during a 15-min period of yoga respiration, despite the peak Pm changes in response to added loads were then significantly reduced. These data suggest that training to yoga respiration selectively increases the respiratory sensation, perhaps through its persistent conditioning of the breathing pattern.     

Wavelets-a new tool in sleep biosignal analysis

SUMMARY  The wavelet transform is a relatively new approach to data processing which has been applied in different areas such as signal, speech and image processing. In the last decade, many papers have been published on wavelet theory and its applications. The wavelet transform provides an elegant alternative to the classical Fourier or Gabor transforms unifying numerous signal processing techniques in a common framework. The purpose of the present paper is to provide an overview of the applicability of the wavelet transform to EEG signal analysis. In the first part of the paper the mathematical background is summarized. In the second part, applications to the sleep EEG field are presented and discussed. The results of these illustrations demonstrate the usefulness of the wavelet transform to solve various problems including signal parametrization, pattern recognition and biosignal representation.