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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
Sun Dec 09 2018
Journal Name
Baghdad Science Journal
Synthesis, Characterization of Poly Heterocyclic Compounds, and Effect on Cancer Cell (Hep-2) In vitro.
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A synthesis series of new heterocyclic derivatives (A2-A7) (pyrrole, pyridazine, oxazine and imidazol) derived from 4-acetyl-2,5-dichloro-1-(3,5-dinitrophenyl)-1H-pyrrole-3-carboxylate(A1) have been synthesised. Synthesis of compound (A2) by the reaction of starting material (A1) with hydroxyl amine hydrochloride in the presence of pyridine. Compound (A2) was reacted with hydrazine hydrate in dry benzene to give (A3) derivative. The compound )A3( deals with sodium nitrite to give diazonium salt, and the reaction diazonium salt with ethyl acetoacetate to produce compound (A4). To a mixture of compound (A4) and hydroxyl amine with sttired to yield (A5).Compound (A6) was prepared by reaction compound (A4) with thiosemicarbazide in presence

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Publication Date
Wed Nov 28 2018
Journal Name
International Journal Of Engineering &amp; Technology
Modified Strut Effectiveness Factor for FRP-Reinforced Concrete Deep Beams
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A few examinations have endeavored to assess a definitive shear quality of a fiber fortified polymer (FRP)- strengthened solid shallow shafts. Be that as it may, need data announced for examining the solid profound pillars strengthened with FRP bars. The majority of these investigations don't think about the blend of the rigidity of both FRP support and cement. This examination builds up a basic swagger adequacy factor model to evaluate the referenced issue. Two sorts of disappointment modes; concrete part and pulverizing disappointment modes were examined. Protection from corner to corner part is chiefly given by the longitudinal FRP support, steel shear fortification, and cement rigidity. The proposed model has been confirmed util

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Publication Date
Mon Jan 01 2018
Journal Name
Proceedings Of The 10th International Joint Conference On Computational Intelligence
Deep Classifier Structures with Autoencoder for Higher-level Feature Extraction
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Publication Date
Fri Dec 30 2016
Journal Name
Al-kindy College Medical Journal
Deep Vein Thrombosis Predisposing Factors Analysis Using Association Rules Mining
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Background: DVT is a very common problem with a very serious complications like pulmonary embolism (PE) which carries a high mortality,and many other chronic and annoying complications ( like chronic DVT, post-phlebitic syndrome, and chronic venous insufficiency) ,and it has many risk factors that affect its course, severity ,and response to treatment. Objectives: Most of those risk factors are modifiable, and a better understanding of the relationships between them can be beneficial for better assessment for liable pfatients , prevention of disease, and the effectiveness of our treatment modalities. Male to female ratio was nearly equal , so we didn’t discuss the gender among other risk factors. Type of the study:A cross- secti

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Publication Date
Thu Jun 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
An optimized deep learning model for optical character recognition applications
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The convolutional neural networks (CNN) are among the most utilized neural networks in various applications, including deep learning. In recent years, the continuing extension of CNN into increasingly complicated domains has made its training process more difficult. Thus, researchers adopted optimized hybrid algorithms to address this problem. In this work, a novel chaotic black hole algorithm-based approach was created for the training of CNN to optimize its performance via avoidance of entrapment in the local minima. The logistic chaotic map was used to initialize the population instead of using the uniform distribution. The proposed training algorithm was developed based on a specific benchmark problem for optical character recog

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Publication Date
Tue Jan 01 2019
Journal Name
International Journal Of Machine Learning And Computing
Facial Emotion Recognition from Videos Using Deep Convolutional Neural Networks
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Its well known that understanding human facial expressions is a key component in understanding emotions and finds broad applications in the field of human-computer interaction (HCI), has been a long-standing issue. In this paper, we shed light on the utilisation of a deep convolutional neural network (DCNN) for facial emotion recognition from videos using the TensorFlow machine-learning library from Google. This work was applied to ten emotions from the Amsterdam Dynamic Facial Expression Set-Bath Intensity Variations (ADFES-BIV) dataset and tested using two datasets.

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Publication Date
Sun Jan 01 2023
Journal Name
Computers, Materials &amp; Continua
Hybrid Deep Learning Enabled Load Prediction for Energy Storage Systems
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Publication Date
Tue Jun 25 2024
Journal Name
World Academy Of Sciences Journal
Expression of programmed death ligand 1 in patients with triple‑negative breast cancer: Association with clinicopathological parameters
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The utilization of targeted therapy for programmed death ligand 1 (PD‑L1) has emerged as a prominent focus in contemporary clinical trials, particularly in the context of immune checkpoint inhibitors. The prognostic significance of the expression of PD‑L1 in invasive mammary cancer remains a subject of discussion in clinical oncology, requiring further exploration, despite its recognition as a biomarker for responsiveness to anti‑PDL1 immunotherapy. The present study was conducted to investigate the immunohistological expression of PD‑L1 in women with triple‑negative breast cancer (TNBC), with a particular focus for searching for the associated clinical and pathological characteristics. The present retrospective study examined the

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Publication Date
Sun Oct 06 2024
Journal Name
Ukrainian Journal Of Nephrology And Dialysis
Effect of Lactobacillus supernatant on swarming-related gene expression in Proteus mirabilis isolated from urinary tract infections
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Proteus mirabilis isolates have been intensively researched for their capacity to cause urinary tract infections (UTIs) and their swarming motility, although little is known about this phenomenon. Probiotic Lactobacillus species, which are beneficial bacteria, are being studied worldwide as therapeutic and preventative agents against bacterial infections. This study investigated Lactobacillus supernatants as a potential new treatment against Proteus mirabilis. In addition to testing their antimicrobial and anti-swarming activities, the research also aimed to understand the genetic mechanisms behind the observed phenotypic changes. Methods. A total of 150 urine specimens were collected from UTI patients at various hospitals in Baghdad. Dire

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Publication Date
Fri Nov 01 2024
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Cytokine
Lupeol stimulates iNOS, TNF-α, and IL-10 expression in the U937 cell line infected with old-world Leishmania donovani
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