In study of effective bioactive compounds, we have synthesized the Co((ІІ), Mn(ІІ), Fe(ІІ), Cu(ІІ), Ni(ІІ), and Zn(ІІ) complexes of the Schiff base derived from trimethoprim and2'-amino-4-chlorobenzophenone and characterized by spectroscopic (NMR, IR, Mass, UV–vis,), analytical, TGA studies and magnetic data .The solution electronic spectral study suggests the stoichiometry of the synthesized complexes and Elemental analysis detected the square planer and octahedral geometry of the compounds. The prepared metal complexes presented promoted efficiency versus the screened bacterial (Escherichia Coli and Staphylococcus aureus) antibacterial efficacy against (Staphylococcus aureus, Salmonella spp., E. coli, Vibrio spp., Pseudomona

Rapid and accurate identification of Methicillin Resistant Staphylococcus aureus is essential in limiting the spread of this bacterium. The aim of study is the detection of Methicillin Resistant Staphylococcus aureus (MRSA) and determining their susceptibility to some antimicrobial agent. A total of fifty clinical Staphylococcus aureus, isolated from the nose of health work staff in surgery unit of Kalar general hospital and from ear of patients attended to the same hospital. The susceptibilities of isolates were determined by the disc diffusion method with oxacillin (1 ?g) and cefoxitin (30 ?g), and by the mannitol salt agar supplemented with cefoxitin (MSA-CFOX), susceptibilities of isolates to other antimicrobial agent were determined b

Lymphoma is a cancer arising from B or T lymphocytes that are central immune system ‎components. It is one of the three most common cancers encountered in the canine; ‎lymphoma affects middle-aged to older dogs and usually stems from lymphatic tissues, ‎such as lymph nodes, lymphoid tissue, or spleen. Despite the advance in the management of ‎canine lymphoma, a better understanding of the subtype and tumor aggressiveness is still ‎crucial for improved clinical diagnosis to differentiate malignancy from hyperplastic ‎conditions and to improve decision-making around treating and what treatment type to use. ‎This study aimed to evaluate a potential novel biomarker related to iron metabolism,

Wildfire risk has globally increased during the past few years due to several factors. An efficient and fast response to wildfires is extremely important to reduce the damaging effect on humans and wildlife. This work introduces a methodology for designing an efficient machine learning system to detect wildfires using satellite imagery. A convolutional neural network (CNN) model is optimized to reduce the required computational resources. Due to the limitations of images containing fire and seasonal variations, an image augmentation process is used to develop adequate training samples for the change in the forest’s visual features and the seasonal wind direction at the study area during the fire season. The selected CNN model (Mob