Abstract

            Itraconazole is a triazole antifungal given orally for the treatment of oropharyngeal and vulvovaginal candidiasis, for systemic infections including aspergillosis, candidiasis,  and for the prophylaxis of fungal infections in immunocompromised patients.

           The study aimed to formulate a practical water-insoluble Itraconazole, with insufficient bioavailability as nanosuspension to increase aqueous solubility and improve its dissolution and oral bioavailability.

          Itraconazole nanosuspension was produced by a

To determine the abilities of salivary E‐cadherin to differentiate between periodontal health and periodontitis and to discriminate grades of periodontitis.

Background: Chronic kidney disease is a condition that results from an indefinite change in the structure and function of the kidneys. A slow, steady progression characterizes it and is irreversible.  Objectives: This study aims to evaluate the findings of certain biochemical and hematological tests in samples from Iraqi CKD patients.  Methods: This study included 90 subjects, where 70 patients with chronic kidney disease and 20 healthy individuals. Blood samples were collected from the patients during their visits to Ghazi Al-Hariri Surgical Specialties' Hospital- Medical City, Baghdad, Iraq. Age, sex and body mass index were assessed for each participant followed by renal function tests [serum blood urea, creatinine, uric acid a

Early detection of brain tumors is critical for enhancing treatment options and extending patient survival. Magnetic resonance imaging (MRI) scanning gives more detailed information, such as greater contrast and clarity than any other scanning method. Manually dividing brain tumors from many MRI images collected in clinical practice for cancer diagnosis is a tough and time-consuming task. Tumors and MRI scans of the brain can be discovered using algorithms and machine learning technologies, making the process easier for doctors because MRI images can appear healthy when the person may have a tumor or be malignant. Recently, deep learning techniques based on deep convolutional neural networks have been used to analyze med

In this paper, fire resistance and residual capacity tests were carried out on encased pultruded glass fiber-reinforced polymer (GFRP) I-beams with high-strength concrete beams. The specimens were loaded concurrently under 25% of the ultimate load and fire exposure (an increase in temperature of 700 °C) for 70 min. Subsequently, the fire-damaged specimens were allowed to cool and then were loaded statically until failure to explore the residual behaviors. The effects of using shear connectors and web stiffeners on the residual behavior were investigated. Finite Element (FE) analysis was developed to simulate the encased pultruded GFRP I-beams under the effect of fire loading. The thermal analyses were performed using the general-pu