Background: The Epstein-Barr virus (EBV) relates to the torch virus family and is believed to have a substantial impact on mortality and perinatal events, as shown by epidemiological and viral studies. Moreover, there have been documented cases of EBV transmission occurring via the placenta. Nevertheless, the specific location of the EBV infection inside the placenta remains uncertain. Methods: The genomic sequences connected to the latent EBV gene and the levels of lytic EBV gene expression in placental chorionic villous cells are examined in this work. A total of 86 placentas from patients who had miscarriage and 54 placentas from individuals who had successful births were obtained for analysis. Results: The research employed QPCR to dete

level of effectiveness of Glutathione - S - Transferees (GST), Glutathione peroxides (GPX),Malondialdehyde (MDA) the product of lipid peroxidation and some trace elements ( zinc,seleinum,iron ,copper ) had been measured in sera of (50) women with breast disease.which had been divided to : Control group (25),The first group (A) benign breast tumors (25),the second group (B) breast cancer (25). The results showed a clear moral high level of Glutathione - S - Transferees (GST), Glutathione peroxidase (GPX) , and Malondialdehyde (MDA) level in breast cancer group while a slight increase were observed in the levels of these enzymes and(MDA) in benign breast group. A significant reduction was evident in the levels of selenium and zinc

Disease diagnosis with computer-aided methods has been extensively studied and applied in diagnosing and monitoring of several chronic diseases. Early detection and risk assessment of breast diseases based on clinical data is helpful for doctors to make early diagnosis and monitor the disease progression. The purpose of this study is to exploit the Convolutional Neural Network (CNN) in discriminating breast MRI scans into pathological and healthy. In this study, a fully automated and efficient deep features extraction algorithm that exploits the spatial information obtained from both T2W-TSE and STIR MRI sequences to discriminate between pathological and healthy breast MRI scans. The breast MRI scans are preprocessed prior to the feature

     In this research, silver nanoparticles (AgNPs) were manufactured using aqueous extract of mushroom Pleurotus ostreatus. Anticancer potential of AgNPs was investigated versus human breast cancer cell line (MCF-7). Cytotoxic response was assessed by MTT assay. AgNPs showed inhibition effect at the following concentrations 12.5, 25, 50, 100 and 200 µg/ml versus MCF-7 cell line, and all treatments had a positive result. The MCF-7 cells were inhibited up to 85.14 % at the concentration 200 μg/ml of AgNPs which reduced cells viability to 14.86%, while 12.5 μg/ml of AgNPs caused 24.23% cells inhibition with reduction of cells viability to 75.77%.

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

The work in this paper focuses on the experimental confirming of the losses in photonic crystal fibers (PCF) on the transmission of Q-switched Nd:YAG laser. First HC-PCF was evacuated to 0.1 mbar then the microstructure fiber (PCF) was filled with He gas & gas. Second the input power and output power of Q-switched Nd:YAG laser was measured in hollow core photonic bandgap fiber (HCPCF). In this work loss was calculated in the hollow core photonic crystal fiber (HCPCF) filled with air then N2, and He gases respectively. It has bean observed that the minimum loss obtained in case of filling (HC-PCF) with He gas and its equal to 15.070 dB/km at operating wavelength (1040-1090) nm.

Breast cancer is a disease in which cells in the breast grow out of control. CD200 is a cell surface glycoprotein expressed on many cells, it belongs to the immunoglobulin family (Ig) and have a great role in the regulation of inflammation in autoimmunity. CD200 is the ligand for CD200R1 receptor. To determine if serum level of CD200 and its receptor CD200R1 can be used as a diagnostic and prognostic marker in patients with breast cancer.This case control study was carried out at Oncology Teaching Hospital – Medical city in Baghdad. Six groups were enrolled, four groups were confirmed with breast cancer stage (I, II, III and IV), fifth group (benign) and sixth group was control (healthy individual). Serum is divided to me

Breast cancer (BC) is one of the most frequently observed malignancy in females worldwide. Today, tamoxifen (TAM) is considered as the highly effective therapy for treatment of breast tumors. Oxidative stress has implicated strongly in the pathophysiology of malignancies. This study aimed to investigate the changes in the levels of oxidants and antioxidants in patients with newly diagnosed and TAM-treated BC. Sixty newly diagnosed and 60 TAM-treated women with BC and 50 healthy volunteers were included in this study. Parameters including total oxidant capacity (TOC), total antioxidant capacity (TAC), and catalase (CAT) activity were determined before and after treatment with TAM. The serum levels of TOC and oxidative stress index (OSI) were

In the current study, the researchers have been obtained Bayes estimators for the shape and scale parameters of Gamma distribution under the precautionary loss function, assuming the priors, represented by Gamma and Exponential priors for the shape and scale parameters respectively. Moment, Maximum likelihood estimators and Lindley’s approximation have been used effectively in Bayesian estimation.

Based on Monte Carlo simulation method, those estimators are compared depending on the mean squared errors (MSE’s). The results show that, the performance of Bayes estimator under precautionary loss function with Gamma and Exponential priors is better than other estimates in all cases.