Background: Antioxidant, sedative, anticancer, and antibacterial properties are among the numerous pharmacological characteristics of Galium verum. Aim: The primary goal of this research was to investigate the therapeutic effects of G. verum extract against folic acid-induced acute kidney injury (AKI). Materials and methods: 18 male rats were assigned into three groups:  Control, AKI, and G. verum. AKI was induced by a dose of folic acid (250 mg/kg, i.p.) while G. verum (250 mg/kg) was administrated for 7 consecutive days. Results: G. verum methanol extract contains flavonoids, anthraquinones, tannins, iridoids, triterpen

Twenty bacterial isolates were identified as Staphylococcus aureus collected from wounds and catheters related infections. A capsulated S. aureus isolate was chosen after performing serum soft agar test, for this study Neutropenic mice were challenged with capsulated S. aureus ,and the effect of G-CSF with or without moxifloxacin was studied. The results indicated that the addition of G-CSF to moxifloxacin therapy have a synergistic effect in the killing of the bacteria, while when each G-CSF and moxifloxacin were used seperately have a similar effect on bacterial killing. It was found that the moxifloxacin has the same activity as G_CSF but is less costly than the latter one.

The convergence speed is the most important feature of Back-Propagation (BP) algorithm. A lot of improvements were proposed to this algorithm since its presentation, in order to speed up the convergence phase. In this paper, a new modified BP algorithm called Speeding up Back-Propagation Learning (SUBPL) algorithm is proposed and compared to the standard BP. Different data sets were implemented and experimented to verify the improvement in SUBPL.

Computer-aided diagnosis (CAD) has proved to be an effective and accurate method for diagnostic prediction over the years. This article focuses on the development of an automated CAD system with the intent to perform diagnosis as accurately as possible. Deep learning methods have been able to produce impressive results on medical image datasets. This study employs deep learning methods in conjunction with meta-heuristic algorithms and supervised machine-learning algorithms to perform an accurate diagnosis. Pre-trained convolutional neural networks (CNNs) or auto-encoder are used for feature extraction, whereas feature selection is performed using an ant colony optimization (ACO) algorithm. Ant colony optimization helps to search for the bes

Identifying phenolic compounds in some genera belonging in the Amaranthaceae family by HPLC technique

Burdock ( Arctium lappa), is among the most popular plants in traditional medicine and it is associated with several biological effects. Literature survey revealed the presence of phenylpropanoid compounds .The most widespread are hydroxycinnamic acids ( mainly caffeic acid and chlorogenic acid) and lignans (mainly arctiin and arctigenin). This work will confirm the presence of these compounds in Arctium lappa, cultivated in Iraq, in both root and leaf samples.  The dried plant samples were extracted by soxhlet with 80% methanol then separated the main constituents by thin layer chromatography (TLC) and high performance liquid  chromatography (HPLC). Identification of the isolated compounds wa

Remote sensing provide the best means to monitoring change in vegetation over a wide range of temporal scales over large areas. In this study, the vegetation index which has been applied known as the Stress Related Vegetation Index (STVI) on in the area around the Euphrates River and part of Al-Habbaniyah lake which located at western side of the river in Ramadi city, Al-Anbar province at Iraq to study the vegetation cover changes and detect the areas of changes, using two satellite sensors multispectral images such as TM and ALI, after geometric correction procedure to rectifying these images. The STVI-4 index result was the best than other vegetation indices (STVI-1 and STVI-3) to discriminate the vegetable cover distribution. The diff