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

This work evaluates the influence of combining twisted fins in a triple-tube heat exchanger utilised for latent heat thermal energy storage (LHTES) in three-dimensional numerical simulation and comparing the outcome with the cases of the straight fins and no fins. The phase change material (PCM) is in the annulus between the inner and the outer tube, these tubes include a cold fluid that flows in the counter current path, to solidify the PCM and release the heat storage energy. The performance of the unit was assessed based on the liquid fraction and temperature profiles as well as solidification and the energy storage rate. This study aims to find suitable and efficient fins number and the optimum values of the Re and the inlet tem

In this study negative result of real-time reverse transcription-QPCR (RT-PCR) assay
tests of Influenza virus of nasal screetion and throat swap samples of Iraqi patients
hospitalized with signs and symptoms of an upper respiratory tract infection in Central
Republic Health Laboratory in Iraq were tested for Respiratory Syncytial Virus
infection by RT PCR .Positive samples was 4 out 0f 20 were used .Viral isolation was
done on a monolayer of 70-80% confluent Human Lung Carcinoma Cells (A549) cell
line and incubated at 33ºC for 4 days .Syncytia was observed in 3 positive samples.

     The current study aimed to synthesize silver nanoparticles (Ag NPs) in a safe and eco-friendly biological method using green tea extract, characterize them using UV-vis spectroscopy, FTIR, XRD, FESEM, and AFM tools, then investigate their antioxidant potentials against DPPH and their cytotoxicity toward lymphoma cells using MTT and ethidium bromide/propidium iodide dual staining assays, and their genotoxic capacities by assessing their effects on the gene expression of p53, caspase3, bcl-2, and bax genes by qPCR and DNA fragmentation.  Results confirmed the synthesis of silver nanoparticles; the UV-vis results showed a peak of absorbance at 414 nm; FTIR analysis showed absorbance bel

Background: The anticancer impact of Epigallocatechin gallate (EGCG) the highly active polyphenol of green tea was abundantly studied.  Though, the exact mechanism of its cytotoxicity is still under investigation. Objectives: Hence, the current study designed to investigate the molecular target of EGCG in HepG2 cells on thirteen autophagy- and/or apoptosis- related genes. Methods: The apoptosis detection analyses such as flow cytometry and dual apoptosis assay were used. The genes expression profile was explored by the real-time quantitative-PCR. Results: EGCG increases G0/G1 cell cycle arrest and the real-time apoptosis markers proteins leading to stimulate apoptos