Background: Adenoid cystic carcinoma (ACC) constitutes about 4% of salivary epithelial tumors and is the second common malignant epithelial salivary gland tumor involving both the major and minor salivary glands. Aims of the study is to evaluate immunohistochemical expression of Ki67 and p53 proteins in ACC. Materials and Methods: immunohistochemical analyses of fifteen cases of formalin – fixed paraffin – embedded tissues blocks of ACC of salivary glands using ki67 and p53 antibodies. Results: ki67 was expressed in 6 of 15 ACC (40%) while p53 aberration was demonstrated in 11 of tumor (73.3%). There was a statistically significant difference between the expression of ki67 and p53 proteins in ACC cases (p value = 0.041). Pearson’s cor

A total of 200 clinical samples included Burns and Wounds infections were collected from Baghdad Governorate. Results showed that rate all isolates of P. mirabilis was 31(15.5%) and rate of Burns infections was 14 (45%) and rate of wounds infection 17 (55%). Where was diagnostic based on conventional biochemical tests and confirmed by the Vitek-2 Compact system and the specific primer of the16SrRNA gene, the ability of bacterial isolates to biofilm formation to be studied. It's considered an important virulence factor in Incidence of diseases and play important role in increasing resistance to antibiotic of encased bacteria, by two methods Congo Red Agar method and Microtiter Plate method. The Congo Red Agar method showed that most isolates

Diabetic retinopathy is an eye disease in diabetic patients due to damage to the small blood vessels in the retina due to high and low blood sugar levels. Accurate detection and classification of Diabetic Retinopathy is an important task in computer-aided diagnosis, especially when planning for diabetic retinopathy surgery. Therefore, this study aims to design an automated model based on deep learning, which helps ophthalmologists detect and classify diabetic retinopathy severity through fundus images. In this work, a deep convolutional neural network (CNN) with transfer learning and fine tunes has been proposed by using pre-trained networks known as Residual Network-50 (ResNet-50). The overall framework of the proposed

Sorting and grading agricultural crops using manual sorting is a cumbersome and arduous process, in addition to the high costs and increased labor, as well as the low quality of sorting and grading compared to automatic sorting. the importance of deep learning, which includes the artificial neural network in prediction, also shows the importance of automated sorting in terms of efficiency, quality, and accuracy of sorting and grading. artificial neural network in predicting values and choosing what is good and suitable for agricultural crops, especially local lemons.

were prepared by condensation of 6-R-2amino bcnzothiazol with Salicyldehyde.These Schiff bases were found to reach with maleic anhydride and citraconic to give