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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
Fri Oct 01 2010
Journal Name
Iraqi Journal Of Physics
Investigation of Beta and Gamma Rays Total Interaction Cross Section and Effective Atomic Number for CR-39Nuclear Track Detector
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CR-39 is a solid state nuclear track detector (SSNTD) that has been used in many research areas. In spite of the assumption that the CR-39 detectors are insensitive to beta and gamma rays, irradiation with these rays can have significant effects on the detector properties. In this study, beta and gamma rays mass attenuation coefficients μ/ρ (cm2 g-1) for the CR-39 detector have been measured using NaI(Tl) scintillation spectrometer along with a standard geometrical arrangement in the energy region of (0.546-2.274) MeV beta rays and standard gamma sources having energy 0.356, 0.5697, 0.6617 and 1.063 MeV. The total atomic cross-section (σtot), total electronic cross-section (σT E) and the effective atomic number (Zeff) of gamma rays a

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Publication Date
Mon Jan 01 2024
Journal Name
Aip Conference Proceedings
Comparative analysis of deep learning techniques for lung cancer identification
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One of the diseases on a global scale that causes the main reasons of death is lung cancer. It is considered one of the most lethal diseases in life. Early detection and diagnosis are essential for lung cancer and will provide effective therapy and achieve better outcomes for patients; in recent years, algorithms of Deep Learning have demonstrated crucial promise for their use in medical imaging analysis, especially in lung cancer identification. This paper includes a comparison between a number of different Deep Learning techniques-based models using Computed Tomograph image datasets with traditional Convolution Neural Networks and SequeezeNet models using X-ray data for the automated diagnosis of lung cancer. Although the simple details p

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Publication Date
Tue Jun 01 2021
Journal Name
2021 Ieee/cvf Conference On Computer Vision And Pattern Recognition Workshops (cvprw)
Alps: Adaptive Quantization of Deep Neural Networks with GeneraLized PositS
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Publication Date
Fri Dec 01 2023
Journal Name
Al-khwarizmi Engineering Journal
An Overview of Audio-Visual Source Separation Using Deep Learning
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    In this article, the research presents a general overview of deep learning-based AVSS (audio-visual source separation) systems. AVSS has achieved exceptional results in a number of areas, including decreasing noise levels, boosting speech recognition, and improving audio quality. The advantages and disadvantages of each deep learning model are discussed throughout the research as it reviews various current experiments on AVSS. The TCD TIMIT dataset (which contains top-notch audio and video recordings created especially for speech recognition tasks) and the Voxceleb dataset (a sizable collection of brief audio-visual clips with human speech) are just a couple of the useful datasets summarized in the paper that can be used to test A

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Publication Date
Sat Jun 30 2012
Journal Name
Al-kindy College Medical Journal
Treatment of Nasopharyngeal Carcinoma by Using Deep X-Ray Therapy
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Background: Nasopharyngeal carcinoma (NPC) is one of the most challenging tumors because of their relative inaccessibility and that their spread can occur without significant symptoms with few signs, but Radiotherapy (RT) has a role in treatment of it.
Objectives: To show that RT is still the modality of choice in the treatment of NPC, to study modes of presentations, commonest histopathological types and their percentages, to show differences in the sensitivities of these types to RT and to find out a 5 year survival rate(5YSR) and its relation with lymph node involvement.
Methods: This is a retrospective study of 44 patients with NPC who were treated with routine RT from 1988-2007 at the institute of radiology and nuclear medicin

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Publication Date
Tue Apr 30 2024
Journal Name
International Journal On Technical And Physical Problems Of Engineering
Deep Learning Techniques For Skull Stripping of Brain MR Images
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Deep Learning Techniques For Skull Stripping of Brain MR Images

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Publication Date
Wed Sep 29 2021
Journal Name
Biomass Conversion And Biorefinery
Encapsulated deep eutectic solvent for esterification of free fatty acid
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A novel encapsulated deep eutectic solvent (DES) was introduced for biodiesel production via a two-step process. The DES was encapsulated in medical capsules and were used to reduce the free fatty acid (FFA) content of acidic crude palm oil (ACPO) to the minimum acceptable level (< 1%). The DES was synthesized from methyltriphenylphosphonium bromide (MTPB) and p-toluenesulfonic acid (PTSA). The effects pertaining to different operating conditions such as capsule dosage, reaction time, molar ratio, and reaction temperature were optimized. The FFA content of ACPO was reduced from existing 9.61% to less than 1% under optimum operating conditions. This indicated that encapsulated MTPB-DES performed high catalytic activity in FFA esterificatio

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Publication Date
Wed Nov 02 2016
Journal Name
Australian Journal Of Basic And Applied Sciences
Full synchronization of 2$\times$ 2 optocouplers network using LEDs
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The synchronization of a complex network with optoelectronic feedback has been introduced theoretically, with use of 2×2 oscillators network; each oscillator considered is an optocoupler (LED coupled with photo-detector). Fixing the bias current (δ) and increasing the feedback strength (Ԑ) of each oscillator, the dynamical sequence like chaotic and periodic mixed mode oscillations has been observed. Synchronization of unidirectionally coupled of light emitting diodes network has been featured when coupling strength equal to 1.7×10-4. The transition between non-synchronization and synchronization states by means of the spatio-temporal distribution has been investigated.

Publication Date
Sat Jul 04 2026
Journal Name
Al-adab Journal
Western Hermeneutics and Heritage: A Contemporary Study in the Debate of Understanding and Horizon.
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Publication Date
Thu Jan 16 2020
Journal Name
Indian Journal Of Forensic Medicine & Toxicology
Effect of Addition of Composite Polyamide Micro Particles and Silicone Dioxide NanoParticle on Some Mechanical Properties of Room Temperature Vulcanized Maxillofacial Silicone Elastomer Before and after Artificial Aging
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Background: The most common reason for re-making a maxillofacial prosthesis is the degradation of the mechanical properties of the silicone. Aim of this study: To assess some mechanical properties of VST-50F maxillofacial silicone reinforced with a composite of silicon dioxide nanoparticle and polyamide-6 microparticle before and after artificial aging. Material and Method: Preparing 240 samples tested for tear strength, tensile strength and elongation percentage, hardness, and roughness before and after aging. The Silicon dioxide was added in concentrations of 1% by weight and Polyamide-6 in the concentration of 0.25% and 0.5% by weight to the VST-50F RTV maxillofacial silicone. The one-way ANOVA and post hoc tests were used for inferentia

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