Lung cancer is the most common dangerous disease that, if treated late, can lead to death. It is more likely to be treated if successfully discovered at an early stage before it worsens. Distinguishing the size, shape, and location of lymphatic nodes can identify the spread of the disease around these nodes. Thus, identifying lung cancer at the early stage is remarkably helpful for doctors. Lung cancer can be diagnosed successfully by expert doctors; however, their limited experience may lead to misdiagnosis and cause medical issues in patients. In the line of computer-assisted systems, many methods and strategies can be used to predict the cancer malignancy level that plays a significant role to provide precise abnormality detectio

Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a

We have investigated the photoemission and electronic properties at the PTCDI molecules interface on TiO2 and ZnO semiconductor by means of charge transition. A simple donor acceptor scenario used to calculate the rate for electron transfer of delocalized electronics in a non-degenerately TiO2 and ZnO electrodes to redox localized acceptors in an electrolytic. The dependent of electronic transition rate on the potential at contact of PTCDI with TiO2 and ZnO semiconductors, it has been discussion using TiO2 and ZnO electrodes in aqueous solutions. The charge transfer rate is determining by the overlapping electronic coupling to the TiO2 and ZnO electrodes, the transition energy, potential and polarity media within the theoretical scenario of

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

Uropathogenic specific protein is a genotoxic protein targeting the DNA, leading to mutations and modifications in the normal cell's DNA and subsequently, cancer development. This study aims to determine the prevalence of the usp gene in Uropathogenic Escherichia coli isolated from females with urinary tract infections and study its correlation with biofilm formation. One hundred and five urine specimens were collected from female patients (20 to 55 years old) with urinary tract infections attending hospitals. Traditional laboratory methods using selective and differential culture media were used for initial bacterial isolation and identification, and molecular techniques that targeted a segment of the 16SrRNA gene with a specific primer pa

Background: Odontogenic cysts are characterized by their sluggish growth and ability to enlarge, primarily affecting the oral and maxillofacial tissues. Timely diagnosis and treatment are crucial to prevent potentially serious consequences. The present study aimed to evaluate and compare the immunohistochemical expression of cytokeratin 19 in the epithelium of odontogenic keratocyst, dentigerous, and radicular cysts.

Methods: This study analyzed forty-five formalin-fixed, paraffin-embedded tissue blocks containing odontogenic cysts. The sample consisted of fifteen odontogenic keratocysts, fifteen dentigerous cysts, and

Background: The aim of this study was to evaluate the expression of fibroblast growth factor-2 and Heparanase in salivary pleomorphic adenoma, and to correlate the two studied markers with each other and with clinicopathological parameters including: age, sex, tumor site and histopathological presentation. Methods: Sections of twenty five formalin-fixed paraffin embedded tissue blocks specimens of salivary pleomorphic adenoma were immunostained using monoclonal antibodies (Fibroblast growth factor-2 and Heparanase) to assess their expression in this tumor. Results: The expression of fibroblast growth factor-2 and Heparanase were positive in all pleomorphic adenoma cases (100%). The positive expression of fibroblast growth factor-2 was signi

Periodontitis is one of the most prevalent bacterial diseases affecting man with up to 90% of the global population affected. Its severe form can lead to the tooth loss in 10-15% of the population worldwide. The disease is caused by a dysbiosis of the local microbiota and one organism that contributes to this alteration in the bacterial population is Prophyromonas gingivalis. This organism possesses a range of virulence factors that appear to contribute to its growth and survival at a periodontal site amongst which is its ability to invade oral epithelial cells. Such an invasion strategy provides a means of evasion of host defence mechanisms, persistence at a site and the opportunity for dissemination to other sites in the mouth. However, p