Nonalcoholic fatty liver disease in a group of Iraqi obese children attending children welfare teaching hospital

Background: For decades, the use of naturally accessible materials in treating human disease has been widespread. The goal of this study was to determine the anti-fungal effectiveness /of the lemongrass essential oil (LGEO) versus Candida albicans (C. albicans) adhesion to polymethylmethacrylate (PMMA) materials. Material and methods: LGEO's anti-fungal activity was tested against C. albicans adhesion using the following concentration of LGEO in PMMA monomer (2.5 vol. %, 5 vol. % LGEO) selected from the pilot study as the best two effective concentrations. A total of 40 specimens were fabricated for the candida adherence test and were subdivided into four equal groups: negative control 0 vol. % addition, experimental with 2.5 vol. % and

Aeromonas salmonicida is a fish pathogen and recognized to cause a variety of diseases in humans. There are a few information about A.salmonicida in Iraq and there is no any previous molecular study on it. During the period of December 2017 to May 2018; Sixteen isolates of the A. salmonicida were isolated and identified from 300 common carp (Cyprinus carpio) fishes stomach in aquarium of Erbil city/ Iraq by using manual, automated Vitek 2 compact system, and confirmed by PCR using gene TonB-dependent siderophore (364bp). Antimicrobial susceptibility was determined by disk diffusion method and the results found that all isolates 100% susceptible to imipenem, 100% resistant to nalidixic acid and variable resistan

This study evaluates the flexural behavior of ultra-thin (50 mm) one‑way reinforced‑concrete (RC) slabs retrofitted with near‑surface mounted (NSM) carbon‑fiber‑reinforced polymer (CFRP) rods under quasi‑static loading. T300‑grade CFRP rods (≈4 mm diameter) were bonded in pre‑cut 7 mm × 7 mm grooves using a two‑part epoxy. As a proof-of-concept experimental baseline, three simply‑supported specimens (1000 mm × 500 mm × 50 mm) were tested in a six‑point bending configuration (four applied loads + two reactions): two conventional controls and one strengthened slab. A load‑control rate of ~15 kN/min was applied; the controls were cycled twice and the strengthened slab four times. Relative to the average of

The aim of study was to explore pharmacist insights toward the impact of prospective implementation of the national health insurance program on patients, providers and Iraqi health system.

This was a qualitative study including semi-structured face-to-face (mostly) interviews with experienced pharmacists. The interview guide included open-ended questions about the impact of the national health insurance program on patients and healthcare providers at three levels: quality of services, costs, and frequency of visits. Potential challenges were also discussed. Interviews were conducted in four provinces from March to May 2022. Thematic analysis was used to analyze the interview findings and generate themes and subthemes.

The

The present study aims to detect CTX-M-type ESBL from Escherichia coli clinical isolates and to analyze their antibotic susceptibility patterns. One hundred of E. coli isolates were collected from different clinical samples from a tertiary hospital. ESBL positivity was determined by the disk diffusion method. PCR used for amplification of CTX-M-type ESBL produced by E. coli. Out of 100 E. coli isolates, twenty-four isolates (24%) were ESBL-producers. E. coli isolated from pus was the most frequent clinical specimen that produced ESBL (41.66%) followed by urine (34.21%), respiratory (22.23%), and blood (19.05%).  After PCR amplification of these 24 isolates, 10 (41.66%) isolates were found to possess CTX-M genes. The CTX-M type ESBL

Face Recognition Systems (FRS) are increasingly targeted by morphing attacks, where facial features of multiple individuals are blended into a synthetic image to deceive biometric verification. This paper proposes an enhanced Siamese Neural Network (SNN)-based system for robust morph detection. The methodology involves four stages. First, a dataset of real and morphed images is generated using StyleGAN, producing high-quality facial images. Second, facial regions are extracted using Faster Region-based Convolutional Neural Networks (R-CNN) to isolate relevant features and eliminate background noise. Third, a Local Binary Pattern-Convolutional Neural Network (LBP-CNN) is used to build a baseline FRS and assess its susceptibility to d