Background: the difference in expression of type IV collagen in borderline tumors and ovarian carcinomas has been studied, but the association with adhesion molecules like CD44 have not gain enough interest. Objectives: The purpose of this study is to assess the expression of CD44v6 and type IV collagen status in borderline tumors and invasive ovarian carcinomas and the correlation between them to define the role of these molecules in tumor invasion and metastasis. Type of the study: A cross sectional study Methods: The study included a total of (101) formalin-fixed paraffin-embedded ovarian tissue blocks; of which (19) cases were borderline tumors and (82) cases were overt ovarian carcinomas. Sections from each block were immunohistochemically stained for CD44v6 and type IV collagen. Results: CD44v6 was significantly correlated with FIGO stage of borderline tumors (p=0.001) and ovarian carcinoma (<0.001) and with histological grade of ovarian carcinomas (p=0.004). There was significantly higher expression of type IV collagen in borderline tumors compared to invasive carcinoma(p<0.001) this significance was also seen in correlation to age, stage and grade of the invasive carcinoma, no significant differences in other clinicopathological features were found. There was negative correlation between CD44 v6 & type IV collagen which was statistically significance (P<0.05) in carcinoma but not in borderline tumors. Conclusions: Our data suggest that observed inverse correlation of type IV collagen expression with CD44v6 positivity in surface epithelial tumors indicates that these molecules may cooperate in the invasion and progression of ovarian carcinomas.
Face Recognition Systems (FRS) are increasingly targeted by morphing attacks, where facial features of multiple individuals are blended into a synthetic image to deceive biometric verification. This paper proposes an enhanced Siamese Neural Network (SNN)-based system for robust morph detection. The methodology involves four stages. First, a dataset of real and morphed images is generated using StyleGAN, producing high-quality facial images. Second, facial regions are extracted using Faster Region-based Convolutional Neural Networks (R-CNN) to isolate relevant features and eliminate background noise. Third, a Local Binary Pattern-Convolutional Neural Network (LBP-CNN) is used to build a baseline FRS and assess its susceptibility to d
... Show MoreOptical fiber technology is without a doubt one of the most significant phases of the communications revolution and is crucial to our daily lives. Using the free version (2022) of RP Fiber Calculator, the modal properties for optical fibers with core radii (1.5−7.5) μm, core index (1.44−1.48) and cladding index (1.43−1.47) have been determined at a wavelength of 1000 nm. When the fiber core’s radius is larger than its operating wavelength, multimode fibers can be created. The result is a single-mode fiber in all other cases. All of the calculated properties, it has been shown, increase with increasing core radius. The modes’ intensity profiles were displayed.
The interaction of interplanetary coronal mass ejections (ICME) with each other and with co-rotating interaction regions (CIR) changes their configuration, dynamics, magnetic field and plasma characteristics and can make space weather forecasting difficult. During the period of March 20–25, 2011, the Solar Terrestrial Relation Observatory (
In the present work, a density functional theory (DFT) calculation to simulate reduced graphene oxide (rGO) hybrid with zinc oxide (ZnO) nanoparticle's sensitivity to NO2 gas is performed. In comparison with the experiment, DFT calculations give acceptable results to available bond lengths, lattice parameters, X-ray photoelectron spectroscopy (XPS), energy gaps, Gibbs free energy, enthalpy, entropy, etc. to ZnO, rGO, and ZnO/rGO hybrid. ZnO and rGO show n-type and p-type semiconductor behavior, respectively. The formed p-n heterojunction between rGO and ZnO is of the staggering gap type. Results show that rGO increases the sensitivity of ZnO to NO2 gas as they form a hybrid. ZnO/rGO hybrid has a higher number of vacancies that can b
... Show MoreThe research discussed the possibility of adsorption of Brilliant Blue Dye (BBD) from wastewater using 13X zeolite adsorbent, which is considered a byproduct of the production process of potassium carbonate from Iraqi potash raw materials. The 13X zeolite adsorbent was prepared and characterized by X-ray diffraction that showed a clear match with the standard 13X zeolite. The crystallinity rate was 82.15% and the crystal zeolite size was 5.29 nm. The surface area and pore volume of the obtained 13X zeolite were estimated. The prepared 13X zeolite showed the ability to remove BBD contaminant from wastewater at concentrations 5 to 50 ppm and the removal reached 96.60% at the lower pollutant concentration. Adsorption measurements versus tim
... Show MoreIn this study, the photodegradation of Congo red dye (CR) in aqueous solution was investigated using Au-Pd/TiO2 as photocatalyst. The concentration of dye, dosage of photocatalyst, amount of H2O2, pH of the medium and temperature were examined to find the optimum values of these parameters. It has been found that 28 ppm was the best dye concentration. The optimum amount of photocatalyst was 0.09 g/75 mL of dye solution when the degradation percent was ~ 96 % after irradiation time of 12 hours, while the best amount of hydrogen peroxide was 7μl/75 mL of dye solution at degradation percent ~97 % after irradiation time of 10 hours, whereas pH 5 was the best value to carry out the reaction at the highest degradation percent. In additio
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