A simple and rapid high performance liquid chromatographic with fluorescence detection method for the determination of the aflatoxin B1, B2, G1 and G2 in peanuts, rice and chilli was developed. The sample was extracted using acetonitrile:water (90:10, v/v%) and then purified by using ISOLUTE multimode solid phase extraction. After the pre-column derivatisation, the analytes were separated within 3.7 min using Chromolith performance RP-18e (100–4.6 mm) monolithic column. To assess the possible effects of endogenous components in the food items, matrix-matched calibration was used for the quantification and validation. The recoveries of aflatoxins that were spiked into food samples were 86.38–104.5% and RSDs were <4.4%. The method was

The current study included the separation of three alkaloid compounds from Anastatica Hierochuntica and studied the effect of the these compounds on cancerous cells , specifically liver cancer it was found that compound number one is the most influential or inhibiting at 50 percent followed by compound number three when using concentration of 400 μg/mL.

Introduction: Articaine was developed in 1969, with reported advantages which are increased potency, increased duration of its anesthetic effect and superior diffusion through bony tissue. The effectiveness of using 4% articaine infiltration for extraction of mandibular molar teeth in comparison to 2% lidocaine inferior alveolar nerve block is not settled yet. Aim: The aim of this study was to evaluate the effectiveness of using 4% articaine infiltration for extraction of mandibular molars by comparing it to the use of 2% lidocaine inferior alveolar nerve block in terms of success, the volume of local anesthetic agents and the pain experienced during the procedure. Materials and methods: A prospective randomized controlled study included

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

The isolation and characterization of Escherichia coli O157:H7 strains from 22 out of 174 fecal samples from petting zoo animals representing twenty‐two different species (camel, lion, goats, zebra, bear, baboon monkey, Siberian monkey, deer, elk, llama, pony, horses, fox, kangaroo, wolf, porcupine, chickens, tiger, ostrich, hyena, dogs, and wildcats) were investigated. One petting Al‐Zawraa zoological society of Baghdad was investigated for E. coli O157:H7 over a 16‐month period that spanned two summer and two autumn seasons. Variation in the occurrence of E. coli O157:H7‐positive petting zoo animals was observed, with animals being culture pos