Abstract Inflammation of periodontal tissues is the consequence of interaction between periodontal pathogens and immune system. This is associated with increased expression of inflammatory cytokines, which may exert destructive effect to the periodontal tissues when released over long period. The aim of this study was to chronologically track the homeostasis of oral keratinocytes following removal of periodontal pathogens. This was done by investigating expression of selected inflammatory markers and integrity of epithelial monolayers in vitro. Rat oral keratinocytes were stimulated with heat-killed Fusobacterium nucleatum and Porphyromonas gingivalis over 7-days then bacteria were washed away and epithelial cells re-cultured for 3-

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

This study aimed to investigate the feasibility of treatment actual potato chips processing wastewater in a continuously operated dual chambers microbial fuel cell (MFC) inoculated with anaerobic sludge. The results demonstrated significant removal of COD and suspended solids of more than 99% associated with relatively high generation of current and power densities of 612.5 mW/m³ and 1750 mA/m³, respectively at 100 Ω external resistance.

This study has been carried out in the animal field of the college of agricultural engineering sciences, university of Baghdad, for the period from 12/15/2021 to 1/26 /2022 for 42 d, to investigate the effect of adding different levels of ellagic acid to the diet of broilers, on some physiological characteristics &  oxidation indicators in meat compared to vitamin C in meat,  225 Ross 308 chicks were used, divided randomly to five treatments such us: T1: control group without additives to diet, &  the other T2, T3, T4 was added  ellagic  acid (

Colorectal cancer is a malignant condition that can arise from multiple causative factors. It ranks second, behind lung cancer, as a leading cause of cancer-related deaths worldwide. Extensive research has been conducted to unravel the genetic underpinnings and molecular mechanisms underlying the development of colorectal cancer (CRC). However, epigenetic modifications of histones at the DNA level have become significantly involved in several malignant diseases such as CRC. Hence, this research sought to assess, for the first time locally, the immunoexpression of HDAC-1 and 3 in a group of colorectal patients. Additionally, we explored potential correlations between the expression of HDAC-1, 3 and VEGF. This retrospective study enco

This study aims to identify the impact of social support on breast cancer patients’ psychological rigidity using a sample in Ramallah and al-Bireh. A descriptive correlative approach was adopted to fulfill the goals of the study and a questionnaire consisted of two criteria: social support and psychological rigidity, which was adopted as a tool for data collection for the study. In order to achieve the goals of the study, the researcher selected a convenient sample that consisted of 123 female breast cancer patients in Ramallah and al-Bireh. This sample represented 50% of the original patient population. The study showed that the average estimated percentage of social support and psychological rigidity for women with breast cancer, in

Lung cancer is one of the most serious and prevalent diseases, causing many deaths each year. Though CT scan images are mostly used in the diagnosis of cancer, the assessment of scans is an error-prone and time-consuming task. Machine learning and AI-based models can identify and classify types of lung cancer quite accurately, which helps in the early-stage detection of lung cancer that can increase the survival rate. In this paper, Convolutional Neural Network is used to classify Adenocarcinoma, squamous cell carcinoma and normal case CT scan images from the Chest CT Scan Images Dataset using different combinations of hidden layers and parameters in CNN models. The proposed model was trained on 1000 CT Scan Images of cancerous and non-c