Background: Odontogenic tumors are a diverse group of lesions with a variety of clinical behavior and histopathologic subtypes, from hamartomatous and benign to malignant. The study aimed to examine the clinical and pathological features of odontogenic tumors in Baghdad over the last 11 years (2011–2021). Materials and Methods: The present retrospective study analyzed all formalin-fixed, paraffin-embedded tissue blocks of patients diagnosed with an odontogenic tumor that were retrieved from archives at a teaching hospital/College of Dentistry in Baghdad University, Iraq, between 2011 and 2021. The diagnosis of each case was confirmed by examining the hematoxylin and eosin stained sections by two expert pathologists. Data from patients' case sheets were collected, including age, gender, location, and histopathological information. The type of lesions was evaluated based on the World Health Organization's most recent classification (March 2022). Results: There were 151 odontogenic tumor during this period. The most common type (39.1%) was Solid ameloblastoma. The mandibular tumors (76.8%) were more than the maxillary tumors (23.2%). The female to male ratio was 1.1:1. The most cases are found between the 2nd and 5th decades of life. Conclusions: Solid ameloblastoma was the most common odontogenic tumor, while primordial odontogenic tumor was the rarest, Odontogenic tumors were slightly more common in females than in males, the most common cases occur in the mandible., the outcome of the study gives valuable information regarding the patients' profile and type of odontogenic tumors over 11 years, which could aid in the early diagnosis and enhance the intervention.
An oil spill is a leakage of pipelines, vessels, oil rigs, or tankers that leads to the release of petroleum products into the marine environment or on land that happened naturally or due to human action, which resulted in severe damages and financial loss. Satellite imagery is one of the powerful tools currently utilized for capturing and getting vital information from the Earth's surface. But the complexity and the vast amount of data make it challenging and time-consuming for humans to process. However, with the advancement of deep learning techniques, the processes are now computerized for finding vital information using real-time satellite images. This paper applied three deep-learning algorithms for satellite image classification
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This study compared and classified of land use and land cover changes by using Remote Sensing (RS) and Geographic Information Systems (GIS) on two cities (Al-Saydiya city and Al-Hurriya) in Baghdad province, capital of Iraq. In this study, Landsat satellite image for 2020 were used for (Land Use/Land Cover) classification. The change in the size of the surface area of each class in the Al-Saydiya city and Al-Hurriya cities was also calculated to estimate their effect on environment. The major change identified, in the study, was in agricultural area in Al-Saydiya city compare with Al-Hurriya city in Baghdad province. The results of the research showed that the percentage of the green
Background: Langerhans' cell histiocytosis (LCH) is a group of conditions affecting the reticuloendothelial system. It includes Letterer-Siwe disease, Hand-Schuller-Christian disease and eosinophilic granuloma and most often presents in childhood. Materials and methods: Twenty-five cases of LCH were diagnosed histologically and confirmed by CD1a antibody and assessed immunohistochemically using anti-RANKL and anti-RANK antibodies to evaluate osteoclastogenic mechanism. Results: Regarding jaw cases, there was a significant correlation between CD1a and RANK (P=0.016). While in the skull, highly significant correlation existed between RANK and RANKL (p=0.001). Among the sites, there was no statistically significant difference found for each
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