Background: Head and neck squamous cell carcinoma is the sixth most common cancer world wide. Despite greater emphasis on multi-modality therapy including surgery, radiation and chemotherapy, advanced stage head and neck squamous cell carcinoma continues to have poor 5-year survival rates (0-40%) that have not significantly improved in the last (30) years. To improve outcomes for this deadly disease , It is required a better understanding of the mechanisms underlying head and neck squamous cell carcinoma tumor growth, metastasis, and treatment resistance. This study evaluates the Immunohistochemical expression of E-cadherin and CD44 adhesion molecules in OSCC and to correlate the expression of either marker with each other, with lymph node metastasis and with tumor grade. Materials and methods: Thirty blocks of OSCC were included in this study. An immunohistochemical staining was performed using anti E-cadherinand anti CD44 monoclonal antibodies. Results: Negative immunohistochemical expression of E-cadherin was found in(66.7%)of the cases and only (33.3%)revealed positive immunoexpression. Positive CD44 immunoreaction was seen in(86.7%)of the cases. There was no statistically significant correlation regarding either marker with respect to the tumor stage, grade and lymph node matastasis. Moreover anon-significant correlation was found between the expression of both markers. Conclusions: this study revealed negative E-cadherin expression in two thirds of the cases, while positive CD44 was illustrated in most of them. Non- significant correlation was found regarding the expression of both markers with tumor stage, grade and lymph node status. Inverse significant correlation was found regarding CD44 expression with the clinical presentation of the study sample. In addition, non significant correlation was found between the E-cadherin and CD44 immunoexpression.
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The main objective of present work is to describe the feasibility of friction stir welding (FSW) for
joining of low carbon steel with dimensions (3 mm X 80 mm X 150 mm). A matrix (3×3) of welding
parameters (welding speed and tool rotational speed) was used to see influence of each parameter on
properties of welded joint .Series of (FSW) experiments were conducted using CNC milling machine
utilizing the wide range of rotational speed and transverse speed of the machine. Effect of welding
parameters on mechanical properties of weld joints were investigated using different mechanical tests
including (tensile and microhardness tests ). Micro structural change during (FSW) process was
studied and different welding zones
Identifying breast cancer utilizing artificial intelligence technologies is valuable and has a great influence on the early detection of diseases. It also can save humanity by giving them a better chance to be treated in the earlier stages of cancer. During the last decade, deep neural networks (DNN) and machine learning (ML) systems have been widely used by almost every segment in medical centers due to their accurate identification and recognition of diseases, especially when trained using many datasets/samples. in this paper, a proposed two hidden layers DNN with a reduction in the number of additions and multiplications in each neuron. The number of bits and binary points of inputs and weights can be changed using the mask configuration
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This case series aims to evaluate patients affected with post COVID‐19 mucormycosis from clinical presentation to surgical and pharmacological treatment to improve the disease prognosis.
This case series was conducted at a specialized surgery hospital in Baghdad Medical City for over 10 months. Fifteen cases who had mild to severe COVID‐19 infections followed by symptoms similar to aggressive periodontitis, such as mobility and bone resorption around the multiple maxillary teeth, were included in this case series.
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