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Immunohistochemical expression of angiotensin‐converting enzyme 2 in superficial and deep maxillofacial tissues: A cross‐sectional study
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Abstract<sec><title>Background and Aims

The involvement of maxillofacial tissues in SARS‐CoV‐2 infections ranges from mild dysgeusia to life‐threatening tissue necrosis, as seen in SARS‐CoV‐2‐associated mucormycosis. Angiotensin‐converting enzyme 2 (ACE2) which functions as a receptor for SARS‐CoV‐2 was reported in the epithelial surfaces of the oral and nasal cavities; however, a complete understanding of the expression patterns in deep oral and maxillofacial tissues is still lacking.

Methods

The immunohistochemical expression of ACE2 was analyzed in 95 specimens from maxillofacial tissues and 10 specimens of pulmonary alveolar tissue using a semiquantitative immunohistochemical scoring procedure, taking into account all superficial and deep maxillofacial tissue cells. We also explored the associations of age, gender, and anatomical site with expression scores.

Results

ACE2 was detected in keratinized epithelia (57.34%), non‐keratinized epithelia (46.51%), nasal respiratory epithelial cells (73.35%), pulmonary alveolar cells (82.54%), fibroblasts (63.69%), vascular endothelial cells (58.43%), mucous acinar cells (59.88%), serous acinar cells (79.49%), salivary duct cells (86.26%) skeletal muscle fibers (71.01%), neuron support cells (94.25%), and bone marrow cells (72.65%). Age and gender did not affect the expression levels significantly in epithelial cells (p = 0.76, and p = 0.7 respectively); however, identical cells expressed different protein levels depending on the site from which the specimens were obtained. For example, dorsal tongue epithelia expressed significantly lower ACE2 scores than alveolar epithelia (p < 0.001). A positive correlation was found between ACE2 expression in fibroblasts and epithelial cells (r = 0.378, p = 0.001), and between vascular endothelial and epithelial cells (r = 0.395, p = 0.001).

Conclusion

ACE2 is expressed by epithelial cells and subepithelial tissues including fibroblasts, vascular endothelia, skeletal muscles, peripheral nerves, and bone marrow. No correlation was detected between ACE2 expression and patient age or sex while the epithelial expression scores were correlated with stromal scores.

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Publication Date
Tue Jun 20 2023
Journal Name
Bulletin Of The Iraq Natural History Museum
A COMPARATIVE-MORPHOLOGICAL STUDY OF SKULLS IN TWO SPECIES OF CARNIVOROUS AND HERBIVOROUS MAMMALS
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The skull is one of the largest bones in the body. It is classified into flat bones that maintain the important organic structures; which are the brain, eyes, and tongue. The skull is a strong support for preserving these organs but they are various according to the type of animals and the environments in which they live and the nature of their nutrition. There are many differences among living organisms in terms of the bones in the skull, their difference or disappearance and their length in the shape of the head. The samples were taken from the scientific storage in the Iraq Natural History Research Center and Museum; Cape hare Lepus capensis (Linnaeus, 1758) and Red fox Vulpes vulpes (Linnaeus, 1758) and the study was conducted o

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Publication Date
Wed Sep 15 2021
Journal Name
Geomechanics And Geoengineering
Effect of Deep Remediation and Improvement on Bearing Capacity and Settlement of Piled Raft Foundation Subjected to Static and Cyclic Vertical Loading
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Publication Date
Wed Jan 10 2024
Journal Name
Nanotechnology
Improving the targeted delivery of curcumin to esophageal cancer cells via a novel formulation of biodegradable lecithin/chitosan nanoparticles with downregulated miR-20a and miR-21 expression
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Abstract<p>Nanoencapsulation, employing safe materials, holds substantial promise for enhancing bioactive compounds’ delivery, stability, and bioactivity. In this study, we present an innovative and safe methodology for augmenting the incorporation of the anticancer agent, curcumin, thereby inducing apoptosis by downregulating miR20a and miR21 expression. Our established methodology introduces three pivotal elements that, to our knowledge, have not undergone formal validation: (1) Novel formulation: We introduce a unique formula for curcumin incorporation. (2) Biocompatibility and biodegradability: our formulation exclusively consists of biocompatible and biodegradable constituents, ensuring t</p> ... Show More
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Publication Date
Wed Jul 23 2025
Journal Name
Al–bahith Al–a'alami
Information Pollution in Iraqi Journalism…Study in Causes and Sources - A research drawn from a Master Degree thesis
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Information pollution is regarded as a big problem facing journalists working in the editing section, whereby journalistic materials face such pollution through their way across the editing pyramid. This research is an attempt to define the concept of journalistic information pollution, and what are the causes and sources of this pollution. The research applied the descriptive research method to achieve its objectives. A questionnaire was used to collect data. The findings indicate that journalists are aware of the existence of information pollution in journalism, and this pollution has its causes and resources.

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Publication Date
Sat Apr 01 2023
Journal Name
The Ocular Surface
Detecting dry eye from ocular surface videos based on deep learning
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Publication Date
Wed Mar 15 2023
Journal Name
International Journal Of Advances In Intelligent Informatics
An automatic lip reading for short sentences using deep learning nets
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One study whose importance has significantly grown in recent years is lip-reading, particularly with the widespread of using deep learning techniques. Lip reading is essential for speech recognition in noisy environments or for those with hearing impairments. It refers to recognizing spoken sentences using visual information acquired from lip movements. Also, the lip area, especially for males, suffers from several problems, such as the mouth area containing the mustache and beard, which may cover the lip area. This paper proposes an automatic lip-reading system to recognize and classify short English sentences spoken by speakers using deep learning networks. The input video extracts frames and each frame is passed to the Viola-Jone

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Oil spill classification based on satellite image using deep learning techniques
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 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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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
Indoor/Outdoor Deep Learning Based Image Classification for Object Recognition Applications
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With the rapid development of smart devices, people's lives have become easier, especially for visually disabled or special-needs people. The new achievements in the fields of machine learning and deep learning let people identify and recognise the surrounding environment. In this study, the efficiency and high performance of deep learning architecture are used to build an image classification system in both indoor and outdoor environments. The proposed methodology starts with collecting two datasets (indoor and outdoor) from different separate datasets. In the second step, the collected dataset is split into training, validation, and test sets. The pre-trained GoogleNet and MobileNet-V2 models are trained using the indoor and outdoor se

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Publication Date
Tue Aug 01 2023
Journal Name
Baghdad Science Journal
An Effective Hybrid Deep Neural Network for Arabic Fake News Detection
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Recently, the phenomenon of the spread of fake news or misinformation in most fields has taken on a wide resonance in societies. Combating this phenomenon and detecting misleading information manually is rather boring, takes a long time, and impractical. It is therefore necessary to rely on the fields of artificial intelligence to solve this problem. As such, this study aims to use deep learning techniques to detect Arabic fake news based on Arabic dataset called the AraNews dataset. This dataset contains news articles covering multiple fields such as politics, economy, culture, sports and others. A Hybrid Deep Neural Network has been proposed to improve accuracy. This network focuses on the properties of both the Text-Convolution Neural

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Publication Date
Wed Dec 30 2015
Journal Name
College Of Islamic Sciences
Acquisition provisions in Islamic jurisprudence: A model - a comparative study
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Acquisition provisions in Islamic jurisprudence

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