The invasion and spread of cancer cells are two of the most notable characteristics of malignant tumors. Recent studies suggest that the epithelial-mesenchymal transition (EMT) has been linked to this significant occurrence. It is linked to the absence of the epithelial brow and the presence of mesenchymal facial hair. The aims of the present study were to explore the immunohistochemical staining of vimentin and E-cadherin ex vivo as EMT markers and assess their potential as predictive biomarkers for transitional cell cancer (TCC). In this study, 55 paraffin-embedded biopsies from TCC patients and 10 autopsies that appeared to be normal were included. Immunohistochemistry was used to produce patterns of vimentin and E-cadherin expression. W

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

HBV and HCV are the major causes of chronic liver diseases throughout the world, and constitute a major global health risk. There is accumulated evidence that the imbalance of proinflammatory and anti-inflammatory cytokine production may play an important role in the pathogenesis of viral hepatic infections and may influence the clinical outcome and disease progression. This study was undertaken to analyze the circulating levels of Tumor Necrotic Factor (TNF-α) and Th2 cytokine IL-10 in patients infected with Hepatitis B and C virus. The study population consisted of 30 patients with chronic HBV, in addition to other 30 patients with chronic HCV infection were recruited on their first examination at the Al-Kindy General Hospital in Baghdad

A sensitive spectrophotometric method was developed for the estimation of cefdinir (CFD), a cephalosporin species. This study involves two methods, and the first method includes the preparing of azo dye by the reaction of CFD diazonium salt with 4-Tert-Butylphenol (4-TBP) and 2-Naphthol (2-NPT) in alkaline medium, which shows colored dyes measured at λmax 490 and 535 nm, respectively. Beer's law was obeyed along the concentration range of (3-100) μg.ml-1. The limits of detection were 0.246, 0.447 μg.ml-1 and molar absorptivities were 0.6129×104, 0.3361×104 L.mol-1cm-1 for (CFD-4-TBP) and (CFD-2-NPT), respectively. The second method includes preconcentration for cefdinir dyes by using cloud point extraction in the presence of Triton

This research presents a study in ultra-desulfurization of diesel fuel produced from conventional hydro desulfurization process, using oxidation and solvent extraction techniques. Dibenzothiophene (DBT) was the organosulfur compound that had been detected in sulfur removal. The oxidation process used hydrogen peroxide as an oxidant and acetic acid as homogeneous catalyst . The solvent extraction process used acetonitrile (ACN) and N-methyl – 2 - pyrrolidone (NMP) as  extractants . Also the effect of five parameters (stirring speed :150 , 250 , 350 , and 450) rpm, temperature (30 , 40 , 45 , and 50) ^oC, oxidant/simulated diesel fuel ratio (0.5 , 0.75 , 1 , and 1.5) , catalyst/oxidant ratio(0.125,0.25,0.5

Objective: Evaluate the effects of different storage periods on flexural strength (FS) and degree of conversion (DC) of Bis-Acryl composite and Urethane dimethacrylate provisional restorative materials. Material and Methods: A total of 60 specimens were prepared from four temporary crown materials commercially available and assigned to four tested groups (n = 15 for each group): Prevision Temp, B&E CROWN, Primma Art, and Charm Temp groups. The specimens were stored in artificial saliva, and the FS was tested after 24 h, 7 d, and 14 d. A standard three-point bending test was conducted using a universal testing machine. Additionally, the DC was determined using a Fourier transform infrared spectroscopy (FTIR) device. The data were analyzed st

This study aims at recognizing Pesticides and how the process of pesticides biodegradation by microbiology took place, and the effect of environmental condition on this process. And how the research uncovered the efficiency of microbiology in the biodegradation process of pesticides, as the perfect temperature for the biodegradation process is 40 °C and humidity effect on pesticides efficiency, when high humidity reduces pesticide efficiency and the perfect acidity to increase bacteria efficiency is 7, for the incubation period, it was found during the previous studies that the best incubation period is 5-7 days, in this period the bacteria imprint on pesticides and increase biodegradation of it.