Rheumatoid arthritis is an inflammatory chronic disease with an autoimmune pathogenesis. To determine the role of Helicobacter pylori as a trigger agent, twenty five patients with rheumatoid arthritis of ages (15-47) years have been investigated and compared with twenty healthy individuals. All the studied groups were carried out to measure the rheumatoid arthritis (RA) IgM, anti-CCP antibody IgG and IgA by ELISA test and by measured anti-IgG antibody level of H. pylori by using ELISA and IFAT techniques. The present study showed significant differences (P< 0.05) of anti-H. Pylori in sera of RA patients than control group, this lead to suggest that H. pylori had a role in pathogenesis of RA.

The relationship between chronic hepatitis B virus and Helicobacter pylori infection was evaluated to determine, seventy five patients with chronic hepatitis B infection (8-70 years) were investigated. The results were compared with the results of 50 healthy volunteers. Anti-H. pylori antibodies IgA and IgG were measured by Indirect fluorescent antibody test (IFAT) in sera of patients and healthy groups. The percentage of anti-H.pylori IgA antibodies (26.67%) were significantly (P<0.01) higher than healthy control group. While, no significant difference was found between the percentages of anti-H. pylori IgG antibodies (48 %) in patient sera and these kind of antibodies in sera of healthy control group (P > 0.05). The present results indica

The study conducted to investigate the association between Helicobacter pylori infection and eye diseases (Glaucoma, Cataract, CSR and Uveitis). One hundred and four patients with multiple eye disorders (10-80) years were observed from 10/9/2020 to 18/11/2020 and compared to thirty-one healthy people (19 female and 12 male). Each participant was tested for H. pylori CagAAbs and TNF-α using an enzyme-linked immunosorbent assay (ELISA). The results have shown that there was a non-significant difference (p≥0.05) in the concentration of CagAantibodies in sera of patients with eye diseases except in the case of CSR (central serous chorioretinopathy), which was a significant difference (P≤0.05) compared to the control group. Also, the result

Support vector machines (SVMs) are supervised learning models that analyze data for classification or regression. For classification, SVM is widely used by selecting an optimal hyperplane that separates two classes. SVM has very good accuracy and extremally robust comparing with some other classification methods such as logistics linear regression, random forest, k-nearest neighbor and naïve model. However, working with large datasets can cause many problems such as time-consuming and inefficient results. In this paper, the SVM has been modified by using a stochastic Gradient descent process. The modified method, stochastic gradient descent SVM (SGD-SVM), checked by using two simulation datasets. Since the classification of different ca

In this work, some of new 2-benzylidenehydrazinecarbothioamide derivatives have been prepared by condensation of thiosemicarbazide and different substituted aromatic benzaldehydes in presence of glacial acetic acid to give compounds (1-6), these compounds have characterized by its physical properties and spectroscopic methods. This work also included theoretical study to prove the ability of these compounds as corrosion inhibitors; The program package of Gaussian 09W with its graphical user interface GaussView 5.0 had used for this purpose; the methods of Density Functional Theory (DFT) with basis set of 6-311G (d,p) / hybrid function of B3LYP and semiempirical method of PM3 have been used, the study included theoretical simulation

Multiple linear regressions are concerned with studying and analyzing the relationship between the dependent variable and a set of explanatory variables. From this relationship the values of variables are predicted. In this paper the multiple linear regression model and three covariates were studied in the presence of the problem of auto-correlation of errors when the random error distributed the distribution of exponential. Three methods were compared (general least squares, M robust, and Laplace robust method). We have employed the simulation studies and calculated the statistical standard mean squares error with sample sizes (15, 30, 60, 100). Further we applied the best method on the real experiment data representing the varieties of

􀀑􀀃Pure Cu (CZTSe) and Ag dopant CZTSe (CAZTSe) thin films with Ag content of 0.1 and 0.2 were fabricated on coring glass substrate at R.T with thickness of 800nm by thermal evaporation method. Comparison between the optical characteristics of pure Cu and Ag alloying thin films was done by measuring and analyzing the absorbance and transmittance spectra in the range of (400-1100)nm. Also, the effect of annealing temperature at 373K and 473K on these characteristics was studied. The results indicated that all films had high absorbance and low transmittance in visible region, and the direct bang gap of films decreases with increasing Ag content and annealing temperature. Optical parameters like extinction coefficientrefractive index, and

The study aimed to assess the expression of CD49d and CD26 in newly diagnosed CLL patients and find their correlation with clinical Binet stage, and other clinical parameters. This study was conducted on 51 newly diagnosed CLL patients based on lymphocyte count > 5×109/L and immunophenotyping. The expression of CD49d, and CD26 were investigated using eight-color flow cytometer. The expression of CD49d and CD26 were detected in 56.9 %, 68.8 % of CLL patients, respectively. The correlation between CD49d expression and CD26 expression was statistically significant (p < 0.001) with high concordance rate between them. The positive expression of both CD49d and CD26 had statistically significant association with clinical Binet staging (p < 0.001,

 A mixture model is used to model data that come from more than one component. In recent years, it became an effective tool in drawing inferences about the complex data that we might come across in real life. Moreover, it can represent a tremendous confirmatory tool in classification observations based on similarities amongst them. In this paper, several mixture regression-based methods were conducted under the assumption that the data come from a finite number of components. A comparison of these methods has been made according to their results in estimating component parameters. Also, observation membership has been inferred and assessed for these methods. The results showed that the flexible mixture model outperformed the others