Background:Periodontal diseases and dental caries are the most common oral diseases, but they can be adequately prevented by adopting a specific health behavior and plaque control.The study was carried out to determine and compare oral health status; it included both caries experience, gingival health and oral hygiene behavior betweenfirst and fifth yearsof Al-Mustansiriyahdental students. Materials and methods: Total sample of the study consisted of 50 students at first year (25 males, 25 females)and 60 students at fifth year (30 males, 30 females). Plaque andgingival indices,dental caries indices (DMFS and DMFT) wererecorded to evaluateoral health status for each student. Further questionnaires were given to evaluate different oral hyg

Objectives To determine the prevalence of oral lesions by age and gender among the pediatric population in Iraq. Materials and methods A review of the archives of the oral pathology department of Baghdad University from, 1970 Materials and Methods: A review of the archives of the oral pathology department of Baghdad University from 1970 to 2013 for all biopsies from children aged 0–15 years old. Results A total of 1286 child specimens represented 11.98% of all biopsied lesions. The pyogenic granuloma was the most frequent lesion in children, and the periapical cyst was the most frequent lesion from an odontogenic origin. The incidence of malignant lesions was higher in the 0–3 age group than other groups. Conclusions The majority of les

Purpose: To assess the antioxidant and antineoplastic effects of Hibiscus sabdariffa Linn. on oral squamous cell carcinoma cells. Materials and Methods: Human squamous cell carcinoma HSCC cells were tested for cytotoxicity by a methanol extract of Hibiscus sabdariffa (MEHSP). After 24, 48, and 72 ...

Objective: The objective of the present study was to design and optimize oral fast dissolving film (OFDF) of practically insoluble drug lafutidine in order to enhance bioavailability and patient compliance especially for a geriatric and unconscious patient who are suffering from difficulty in swallowing.Methods: The films were prepared by a solvent casting method using low-grade hydroxyl propyl methyl cellulose (HPMC E5), polyvinyl alcohol (PVA), and sodium carboxymethyl cellulose (SCMC) as film forming polymers. Polyethylene glycol 400 (PEG400), propylene glycol (PG) and glycerin were used as a plasticizer to enhance the film forming properties of the polymer. Tween 80 (1% solution) and poloxamer407 were used as a surfactant, citri

Background: Breast cancer is the most common cancer in Iraq and the United Kingdom. While the disease is frequently diagnosed among middleaged Iraqi women at advanced stages accounting for the second cause of cancer-related deaths, breast cancer often affects elderly British women yielding the highest survival of all registered malignancies in the UK. Objective: To compare the clinical and pathological profiles of breast cancer among Iraqi and British women; correlating age at diagnosis with the tumor characteristics, receptor-defined biomarkers and phenotype patterns. Methods: This comparative retrospective study included the clinical and pathological characteristics of (1,940) consecutive female patients who were diagnosed with invasive b

Disease diagnosis with computer-aided methods has been extensively studied and applied in diagnosing and monitoring of several chronic diseases. Early detection and risk assessment of breast diseases based on clinical data is helpful for doctors to make early diagnosis and monitor the disease progression. The purpose of this study is to exploit the Convolutional Neural Network (CNN) in discriminating breast MRI scans into pathological and healthy. In this study, a fully automated and efficient deep features extraction algorithm that exploits the spatial information obtained from both T2W-TSE and STIR MRI sequences to discriminate between pathological and healthy breast MRI scans. The breast MRI scans are preprocessed prior to the feature

Lung cancer is one of the most serious and prevalent diseases, causing many deaths each year. Though CT scan images are mostly used in the diagnosis of cancer, the assessment of scans is an error-prone and time-consuming task. Machine learning and AI-based models can identify and classify types of lung cancer quite accurately, which helps in the early-stage detection of lung cancer that can increase the survival rate. In this paper, Convolutional Neural Network is used to classify Adenocarcinoma, squamous cell carcinoma and normal case CT scan images from the Chest CT Scan Images Dataset using different combinations of hidden layers and parameters in CNN models. The proposed model was trained on 1000 CT Scan Images of cancerous and non-c

This study represents an optical biosensor for early skin cancer detection using cysteine-cupped CdSe/CdS Quantum Dots (QDs). The study optimizes QD synthesis, surface, optical functionalization, and bioconjugation to enhance specificity and sensitivity for early skin cancer cell detection. The research provides insights into QD interactions with skin cancer biomarkers, demonstrating high-contrast, precise cellular imaging. Cysteine-capped CdSe/CdS absorption spectra reveal characteristic peaks for undamaged DNA, while spectral shifts indicate structural changes in skin-cancer-damaged DNA. Additionally, fluorescence spectra show sharp peaks for undamaged DNA and notable shifts and intensity variations when interacting with skin cancer. This