Background: Cutaneous leishmaniasis (CL) is a neglected disease in tropical countries, including Iraq. Several studies have sought to examine chemotherapies for leishmaniasis treatment but most of them are of toxic and/or undesirable side effect, therefore, the need for investigating new fewer toxic therapies is essential. Aim of study: In this study, the cytotoxic effect of Artemisinin (ART), a novel herbal compound, was screened against the two forms, promastigotes and amastigotes, of the Iraqi isolate of Leishmania tropica, the causative agent of Baghdad boil. Material and methods:  Different concentrations (1000, 500, 250, 125, 62.5, 31.25, 15.6 and 7.8) µM of Artemisinin were screened to investigate the leishmanic

Background: Periodontal diseases are initiated by microbial plaque, which accumulates in the sulcular region and induces an inflammatory response. The Receptor activator of nuclear factor-kappa B ligand / osteoprotegerin (RANKL/OPG) axis is involved in the regulation of bone metabolism in periodontitis, in which an increase in receptor activator of nuclear factor-kappa B ligand or a decrease in osteoprotegerin can tip the balance in favor of osteoclastogenesis and the resorption of alveolar bone that is the hallmark of periodontitis. This study was performed to investigate the role of salivary levels of RANKL and OPG in pathogenesis of chronic periodontitis. Subjects and Methods: Fifty five subjects with chronic periodontitis with ages rang

Background: Stromal inflammatory cells in malignant tissue have recently gained increasing interest. Unlike the extensive research on tumor‐infiltrating lymphocytes, published data about tumor‐infiltrating eosinophils in breast cancer are scarce. Furthermore, similar studies have yet to be conducted in Iraq.

Aims: The objective of this study is to examine the presence of eosinophilic infiltration by direct visualization using light microscopy and to analyze its relationship with other histological parameters in a group of Iraqi women diagnosed with invasive mammary cancer.

Methods and material: A retrospective study enrolled 90 h

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