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.     

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.     

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.     

Alpha-lipoic acid may ameliorate testicular damage by targeting dox-induced altered antioxidant parameters,mitofusin-2 and apoptotic gene expression

In the study, the ameliorating effects of alfa lipoic acid (ALA) against doxorubicin-induced testicular apoptosis, oxidative stress and disrupted mitochondrial fusion were investigated in male rats. Rats were divided into four groups as control, doxorubicin (DOX), DOX + ALA and ALA. A single dose of 15 mg/kg DOX was administered i.p to the DOX and DOX + ALA groups. 50 mg/kg ALA was given to the DOX + ALA and ALA groups by oral gavage every other day. After 28 days, rat testes and serum samples were collected and analysed. Administration of DOX alone caused a decrease in body and relative testicular weights, seminiferous tubule diameter and germinal epithelium thickness, Johnsen's score and serum testosterone levels. DOX treatment led to severe testicular damage such as tubular degeneration, and atrophic tubules. Also, the activities of superoxide dismutase and glutathione peroxidase were reduced, while the level of malondialdehyde was increased in the testis. The mRNA levels of apoptotic-related genes (CASP3, TP53, BAX, BCL2) and apoptotic index were increased, while mitofusin-2 decreased. DOX caused an increase in CASP3 and a decrease in mitofusin-2 immunoreactivities. Treatment with ALA markedly improved all of DOX-induced biochemical, histochemical and molecular alterations in rat testis. Consequently, ALA has a therapeutic role in ameliorating DOX-induced testicular damage in rats.