Objective Thalassemic patients present with multiple immune abnormalities that may predispose them to oral Candida, however this has not been investigated. The aim of this study was to assess oral candidal colonization in a group of patients with β-thalassemia major both qualitatively and quantitatively. Study design The oral mycologic flora of 50 β-thalassemia major patients and 50 age- and sex-matched control subjects was assessed using the concentrated oral rinse technique. Candida species were identified using the germ tube test and the Vitek yeast identification system. Results Oral Candida was isolated from 37 patients (74%) and 28 healthy subjects (56%; P = .04). The mean candidal count was significantly higher in thalassemic patie

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

This experiment was holdup in A-Faris poultry farms from 1st March to 11 of Aprile 2019. (ACTH) hormone infusion was tested in this experiment on acid-base regulation in broiler chickens. For 7 days, osmotic pumps dispensed 8 IU of ACTH in saline/kg of BW/d, or the same volume of saline as in ACTH at 1 l/h. On days 0 and 14, after the beginning of the infusions, blood samples were obtained to establish a baseline. The plasma concentrations of Na+, K+, and Cl- were decreased, whereas the partial pressure of CO2, anion gap, corticosterone, mean corpuscular hemoglobin concentration, and blood concentrations of hemoglobin and HCO - were all elevated due to the ACTH administration. When given ACTH, neither blood pH nor plasma Ca2+ levels changed