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.     

The effect of Bosentan on healing of colonic anastomosis

Background  

Ischemia is the most important factor compromises wound healing in colonic anastomosis. Mesenteric vessels are ligated at first while performing colonic resection and following anastomosis. Therefore blood supply of the related segments of colon temporarily interrupted and ischemia can easily occur. This study was carried out to explore whether Bosentan, an endothelin-receptor antagonist, can eliminate vasoconstruction, increase blood flow in the splanchnic area and anastomotic region and therefore possibly facilitate wound healing and prevent intra-abdominal adhesion formation.     

The rupture through posterior vaginal fornix of the posterior lower uterine segment.

Uterine rupture during labor, when it is in the immediate vicinity of the cervix, frequently extends transversely or obliquely. Usually the tear is longitudinal when it occurs in the portion of the uterus adjacent to the broad ligament. We report an unusual case of uterine rupture through posterior vaginal fornix of the posterior lower uterine segment.     

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.     

<Emphasis Type="Italic">Demodex folliculorum</Emphasis> in patients with rheumatoid arthritis

The objective of this study was to investigate the incidence and density of Demodex folliculorum in the patients with rheumatoid arthritis (RA). Forty-one patients with RA and twenty-seven age and sex matched healthy controls were enrolled in this study. Disease Activity Score (DAS 28) was used for the assessment of disease activity. Out of 41 patients, 33 were females and 8 males. The mean disease duration was 10.9 ± 8.2 years. The mean DAS 28 was 3.8 ± 1.2. No statistically significant differences in the incidence and density of Demodex mites were found between patients with RA and controls. Although immunosuppression is thought to be a risk factor for the D. folliculorum infestation no such correlations could be found in the 41 immunosuppressed patients with RA, therefore, further studies with larger groups are needed.