Background: Recent advancements in molecular techniques have identified over 450 genotypes of Human Papillomavirus (HPV), classified into low- and high-oncogenic risk categories. The rise in high-oncogenic risk HPV genotypes has been linked to various cancers, including those affecting the oral, oropharyngeal, and nasopharyngeal regions in both pediatric and adult populations. Methods: In this study, a cohort of 102 tonsillar tissue samples was included. This comprised 40 specimens from pediatric patients aged 4 to 9 years with nasopharyngeal adenoid hypertrophies, and 42 specimens from pediatric patients aged 5 to 12 years with palatine tonsillar hypertrophies. Among the 82 tonsillar tissue samples analyzed, 38 were from pediatric patients

Background: The oral cavity is considered as a complex ecological niche, its complex microbial community is reflected to it. Streptococcus mutans has been implicated as one of the major etiological factor of dental caries. Tooth surfaces colonized with Streptococcus mutans are at a higher risk for developing caries, while lactobacilli are considered as the secondary invaders, not initiators of the carious lesion. The main purpose of this study was to correlate the dental caries (for primary and permanent teeth) in the upper jaw with the streptococcus mutans and lactobacilli count in the dental plaque and saliva, also to correlate the dental caries (for primary and permanent teeth) in the lower jaw with the streptococcus mutans and lactobaci

The use of Bayesian approach has the promise of features indicative of regression analysis model classification tree to take advantage of the above information by, and ensemble trees for explanatory variables are all together and at every stage on the other. In addition to obtaining the subsequent information at each node in the construction of these classification tree. Although bayesian estimates is generally accurate, but it seems that the logistic model is still a good competitor in the field of binary responses through its flexibility and mathematical representation. So is the use of three research methods data processing is carried out, namely: logistic model, and model classification regression tree, and bayesian regression tree mode

Diabetes mellitus type II is a disorder of metabolism and complex diseases affected by genetic environmental factors and associated with inflammation. The symptoms of type II diabetes develop gradually, which are associated with increased blood concentration of marker of the endothelial inflammatory factors. The expression of adhesion molecules, including E-selectin, intracellular adhesion molecule-1(ICAM-1) and vascular cell adhesion molecule-1 (VCAM-1) on the surface of vascular endothelial cells to help leukocyte stick to other surrounding tissues. Many researchers have made attempts to determine the significance of particular ABO phenotype for the susceptibility to diseases. Many reports show a strong association with the ABO blood grou

Background: This study was designed to measure the displacement pattern of posterior palatal seal (pps) area in different forms of the palate and with different impression techniques. Materials and method: This study was used to measure the displacement pattern of (pps)in different palatal shapes by using different impression materials Korrecta wax No.4,Green compound and design of House for pps for each palatal forms by using a 3D Scanner of CAD/CAM and measuring the distance between 2 points in pps area by using Caural Threw. Result: The results show highly significant differences between these techniques and the control group (impression with light body) Conclusion: The physiological impression technique of pps with Korecta wax no.4

The proliferation of many editing programs based on artificial intelligence techniques has contributed to the emergence of deepfake technology. Deepfakes are committed to fabricating and falsifying facts by making a person do actions or say words that he never did or said. So that developing an algorithm for deepfakes detection is very important to discriminate real from fake media. Convolutional neural networks (CNNs) are among the most complex classifiers, but choosing the nature of the data fed to these networks is extremely important. For this reason, we capture fine texture details of input data frames using 16 Gabor filters indifferent directions and then feed them to a binary CNN classifier instead of using the red-green-blue