Helicobacter pylori infection in epileptic patients.

It is well known that there might be an epidemiological association between Helicobacter pylori infection and extraintestinal diseases. This study aimed at determining H. pylori infection in epileptic patients. Forty-seven cryptogenic epileptic patients (Group 1) and 35 healthy people (Group 2) participated in this study. Presence of H. pylori infection was examined by H. pylori stool antigen (HpSA), H. pylori IgG, and IgM. HpSA was detected in 21 participants (44.6%) in Group 1 and in 3 participants (8.5%) in Group 2. H. pylori IgM was positive in 27 participants (57.4%) in Group 1 and in 8 participants (22.8%) in Group 2. H. pylori IgG was positive in 37 participants (78.7%) in Group 1 and in 13 participants (38%) in Group 2. The difference of rates of HpSA, H. pylori IgM and IgG in Groups 1 and 2 were found statistically significant (chi2=4.18, p=0.04; chi2=9.18, p=0.0017; chi2=14.58, p<0.001, respectively). We also compared presence of H. pylori infection between the epileptic patients with poor and good prognosis; HpSA positivity was detected in 15 (62.5%) of 24 and 6 (26%) of 23, respectively, and the differences were statistically significant (chi2=6.30, p=0.012). H. pylori IgM positivity was detected in 16 (66%) of 24 patients with poor prognosis and 11 (47.8%) of 23 patients with good prognosis (p>0.05). H. pylori IgG positivity was detected in 18 (75%) of 24 patients with poor prognosis and 19 (82.6%) of 23 patients with good prognosis. The differences of H. pylori IgM and IgG positivity rates in epileptic patients with poor and good prognosis were not found statistically significant (p>0.05). These results suggest a probable association between the acute H. pylori infection and epilepsy, especially with poor prognosis.     

Various types of suprameatal spines and depressions in the human temporal bone

Since it covers the lateral wall of the mastoid air system, the suprameatal triangle is of importance to otologic surgeons during mastoidectomy. Because of this clinical importance, topographic anatomy of the suprameatal spine and depression was studied on Anatolian skulls. In all, 363 male and 231 female skulls were studied. The most prevalent type of suprameatal spine resembled a crest and was found in both sexes on the right (77.6%) and left (80%) sides. The absence of a suprameatal depression was significantly higher in females (right 9.1%; left 8.7%) than in males (right 1.7%; left 2.5%). Suprameatal depressions were mostly shallow in female subjects, but were mostly observed in males to be at a medium depth or deep. Received: 5 January 1998 / Accepted: 19 March 1998     

Application of classical and model-based spectral methods to ophthalmic arterial Doppler signals with uveitis disease

In this study, Doppler signals recorded from ophthalmic artery of 75 subjects were processed by PC-computer using classical and model-based methods. The classical method (fast Fourier transform) and three model-based methods (Burg autoregressive, moving average, least-squares modified Yule–Walker autoregressive moving average methods) were selected for processing ophthalmic arterial Doppler signals with uveitis disease. Doppler power spectra of ophthalmic arterial Doppler signals were obtained by using these spectrum analysis techniques. The variations in the shape of the Doppler spectra as a function of time were presented in the form of sonograms in order to obtain medical information. These Doppler spectra and sonograms were then used to compare the applied methods in terms of their frequency resolution and the effects in determination of uveitis disease.     

A mixture of experts network structure for modelling Doppler ultrasound blood flow signals

Mixture of experts (ME) is a modular neural network architecture for supervised learning. This paper illustrates the use of ME network structure to guide modelling Doppler ultrasound blood flow signals. Expectation-Maximization (EM) algorithm was used for training the ME so that the learning process is decoupled in a manner that fits well with the modular structure. The ophthalmic and internal carotid arterial Doppler signals were decomposed into time-frequency representations using discrete wavelet transform and statistical features were calculated to depict their distribution. The ME network structures were implemented for diagnosis of ophthalmic and internal carotid arterial disorders using the statistical features as inputs. To improve diagnostic accuracy, the outputs of expert networks were combined by a gating network simultaneously trained in order to stochastically select the expert that is performing the best at solving the problem. The ME network structure achieved accuracy rates which were higher than that of the stand-alone neural network models.     

Detection of ophthalmic arterial doppler signals with Behcet disease using multilayer perceptron neural network

Doppler ultrasound is known as a reliable technique, which demonstrates the flow characteristics and resistance of ophthalmic arteries. In this study, ophthalmic arterial Doppler signals were obtained from 106 subjects, 54 of whom suffered from ocular Behcet disease while the rest were healthy subjects. Multilayer perceptron neural network (MLPNN) employing delta-bar-delta training algorithm was used to detect the presence of ocular Behcet disease. Spectral analysis of the ophthalmic arterial Doppler signals was performed by least squares (LS) autoregressive (AR) method for determining the MLPNN inputs. The MLPNN was trained with training set, cross validated with cross validation set and tested with testing set. All these data sets were obtained from ophthalmic arteries of healthy subjects and subjects suffering from ocular Behcet disease. Performance indicators and statistical measures were used for evaluating the MLPNN. The correct classification rate was 96.43% for healthy subjects and 93.75% for unhealthy subjects suffering from ocular Behcet disease. The classification results showed that the MLPNN employing delta-bar-delta training algorithm was effective to detect the ophthalmic arterial Doppler signals with Behcet disease.     

Immunohistochemical study on histogenesis of congenital epulis and review of the literature

Congenital epulis is a very rare lesion found only in newborn infants. This tumor is multiple in about 10% of reported cases, rarely with the simultaneous involvement of the maxilla and mandibula, as in this article. In the presented case, light microscopy demonstrated large eosinophilic granular cells arranged in solid nests that are separated by thin fibrovascular areas. The tumors In the maxilla and mandibula were investigated with a panel of polyclonal and monoclonal antibodies, and using immunoperoxidase methods on formalin-fixed, paraffin-embedded sections. Immunohistochemical studies revealed strong and diffuse cytoplasmic staining for neuron specific enolase and vimentin. However, all other reactions were negative. These results suggest that the congenital epulis may be derived from uncommitted nerve-related mesenchymal cells.     

Interpenetrating polymer networks of poly(dimethylsiloxane) with polystyrene,polybutadiene and poly(glycerylpropoxytriacrylate)

The synthesis of full and semi interpenetrating networks (IPNs) based on poly(dimethy1-siloxane) (PDMS)/polystyrene, PDMS/polybutadiene and PDMS/poly(glycerylpropoxytriacry-late) 1

1 Glycerylpropoxytriacrylate (GFTA):

is described. PDMS was used as host polymer in most cases. PDMS networks were prepared with two prepolymers having different number-average molecular weights between junctions, M?_c = 15 · l0³ and M?_c = 75 · l0³. Physical properties of IPN samples such as stress-strain behaviour, swelling and glass transition temperature (T_g) were examined. IPNs of both PDMS/polystyrene and PDMS/poly(glycerylpropoxytriacrylate) exhibit superior mechanical and elastomeric properties with respect to pure PDMS network. Most of the IPN systems studied in this work display two T_gs and indicate phase separation.