Human cystic echinococcosis caused by Echinococcus granulosus is one of most important and widespreadparasitic zoonoses in the world. The present study was aimed to identify the immunomodulatory activity ofaqueous extract of Cordia myxa fruit since this plant considers one of medically important plants, which is widely used for treatment of numerous diseases, that correlate with the effectiveness of immunized by hydatid cyst fluid antigen HCFAg. Forty Balb/c mice were divided into equal groups, first group was immunized with HCFAg, the second group was treated with aqueous extract of C. muxa fruit, the third group was immunized and treated, the fourth group was as a control. Delayed type hypersensitivity (DTH), Mitotic index (MI) and histop

Abstract

In this manuscript, a simple new method for the green synthesis of platinum nanoparticles (Pt NPs) utilizing F. carica Fig extract as reducing agent for antimicrobial activities was reported. Simultaneously, the microstructural and morphological features of the synthesized Pt NPs were thoroughly investigated. In particular, the attained Pt NPs exhibited spherical shape with diameter range of 5-30 nm and root mean square of 9.48 nm using Transmission Electron Microscopy (TEM) and Atomic Force Microscopy (AFM), respectively. Additionally, the final product (Pt NPs) was screened as antifungal and antibacterial agent against Candida and Aspergillus species as well as Gram-positive Staphyllococcus aureus and G

Background: The use of antiepileptic drugs (AEDs) during pregnancy warrants several side effects and also deleterious effects on fetal development, the antiepileptic drugs have potential to affect the fetal development throughout the pregnancy although, the majority of infants born to epileptic pregnant women are normal but more expose to the malformations. Aim: The present study aimed to investigate the effect of carbamazepine drug on the kidney development at day 7 postnatally in the Albino Rat (Rattus rattus) as a mammalian model. Material & Methods: 20 healthy pregnant female rats were divided into two groups, 10 pregnant rats in each group; group one served as control group administrated distal water while group two used as experimenta

The purpose of this study was to examine the association of oral administration of Carbamazepine during pregnancy and the histological changes in the ovaries of mice. Timed-pregnant mice were divided into experimental and control groups. 60 mice in the experimental group received daily oral of 15 mg/kg of carbamazepine via intragastric tube on gestational days 0 to 18. 20 mice were used as control group. They received normal saline via the same route. Dams underwent laparotomy on pregnancy days 13, 15, and 18 and the ovaries were collected. Routine histological processing of the ovaries histology of paraffin sections stained with haemotoxylin and eosin, were conducted. The ovary under the effect of the drug, there was signs of degeneration

سمير خلف فياض * و محسن طالب د.نوال عزت عبد اللطيف*, مجلة الهندسة والتكنولوجيا, 2010

<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol

Manual fruit picking is labor-intensive and can damage fruit. Fully mechanized picking is efficient, but it also risks fruit damage. Therefore, semi-automated tools are needed to improve bitter orange picking. This paper presents a smart manual picker designed to facilitate picking while predicting fruit maturity based on picking force as well as various chemical and physical parameters using machine learning (ML). The study methodology consists of five stages: (1) manufacturing the smart picker, (2) picking 50 bitter orange samples, (3) measuring the characteristics of the bitter oranges in the laboratory, (4) training different ML models, and (5) identifying the most accurate model for predicting fruit maturity. The results indicate that