Objectives Acid sphingomyelinase deficiency (ASMD) is an inherited autosomal recessive disease caused by pathogenic variants in the sphingomyelin phosphodiesterase-1 (SMPD1) gene, which encodes acid sphingomyelinase (ASM). ASMD has 3 broad phenotypes (type A, type A/B, and type B) characterized by the age of onset, symptomatology, and the rapidity of disease progression. The diagnosis of ASMD can be delayed or missed because of the wide spectrum of severity and its variable manifestations. Analysis of genotype-phenotype correlations can help to determine ASMD disease type and inform management. Here, we describe the clinical presentation of 47 patients with ASMD referred to a single center in Iraq since 2007, whose diagnosis was confirmed b

Abstract Background: Colorectal cancer (CRC) is a leading cause of cancer mortality worldwide. Identifying novel biomarkers is critical for improving diagnosis, prognosis, and treatment strategies. This study investigates the serum levels of kisspeptin-1 (KISS1), its receptor (KISS1R), growth differentiation factor 15 (GDF15), and carcinoembryonic antigen (CEA) in Iraqi CRC patients. Objectives: Explore associations between serum levels of Kiss1, Kiss1R, GDF, and CEA and disease progression in Iraqi patients with CRC. Methods: A case-control study was conducted, including 72 CRC patients and 36 healthy controls. Patients were stratified into non-metastatic and metastatic groups. Serum biomarker levels were measured using enzyme-link

Objectives: To determine the impact of an educational program on nurses’ knowledge
and practices concerning neurogenic bladder rehabilitation for spinal cord injured persons
through a follow-up approach each two months post program implementation for six
months.
Methodology: "Follow-up" longitudinal design by using time series approach of data
analysis and the application of pre-post tests approach for the study and the control
groups. The study was carried out at Ibn Al-Kuff hospital for (SCI) in Baghdad governorate
from 5th of July 2010 to 15th of October 2011. To achieve the objectives of the study, a
non-probability (purposive) sample of (60) nurses (males and females) were working in SCI
units were selec

This investigation integrates experimental and numerical approaches to study a novel solar air heater aimed at achieving an efficient design for a solar collector suitable for drying applications under the meteorological conditions of Iraq. The importance of this investigation stems from the lack of optimal exploitation of solar energy reaching the solar collector, primarily attributable to elevated thermal losses despite numerous designs employed in such solar systems. Consequently, enhancing the thermal performance of solar collectors, particularly those employed in crop drying applications, stands as a crucial focal point for researchers within this domain. Two identical double-pass solar air heaters were designed and constructed for

In this study, thin film of pure zinc oxide (ZnO) and ZnO doped with Ga2O3 films with different concentrations (0, 0.03, 0.05, 0.07 and 0.09)wt% were prepared by pulsed laser deposition. The powder mixture was then sintered in a furnace at 1273 K for 5 h. The resulting powders were thoroughly ground and then pressed using a special press to form discs with a diameter of 1 cm and a thickness of 0.5 cm. The deposition was carried out under a vacuum of 2.5×10−2 mbar on various substrates, including glass for AFM measurements and n-type crystalline silicon wafers for the gas sensor. AFM results revealed a progressive increase in both grain size and roughness with moderate doping and irregularity at high doping levels. Gas-sensing meas

     The oral cavity has the second major and most diverse microflora after the gut. Since it is the starting point of digestion; the oral microbiota is essential for maintaining oral and systemic health.  Thus, this study aimed to find the bacterial isolates which act as a causative agent of periodontal diseases in Iraqi patients and their relation with some immune oral parameters. Saliva specimens and oral swabs of 91 patients (51) and control individuals (40) were collected in this study. The specimens of patients were collected from Al-Amirya and Almaamon Specialized Dental Centers in Baghdad for a period from November/2021 to February/2022. The microbiological results revealed, that the most prevalent bacterial isolates we

This paper proposes a hybrid artificial intelligence (AI) model that combines an Artificial Neural Network (ANN) and Particle Swarm Optimization (PSO) to predict the Quality of Service (QoS) in 5G networks. The model utilizes radio channel indicators such as Reference Signal Received Power (RSRP), Reference Signal Received Quality (RSRQ), Received Signal Strength Indicator (RSSI), and Channel Quality Indicator (CQI) to forecast throughput and latency levels. These indicators are critical factors affecting network performance; however, the nonlinear relationship among them makes traditional analytical models inadequate for accurate QoS prediction. The importance of the current study lies in estimating QoS in 5G networks by combining

Water-based drilling fluids (WBDFs) are the industry-preferred medium for drilling reactive shale formations, yet they remain susceptible to shale swelling, fluid invasion, and cuttings dispersion—all of which compromise wellbore stability. Although oil-based fluids (OBFs) provide effective shale inhibition, their high cost and adverse environmental profile limit their use. Nanoparticles (NPs) derived from waste feedstocks offer a low-cost, environmentally responsible alternative for enhancing WBDF performance, but no prior study has simultaneously evaluated both waste-derived SiO2 and Al2O2 NPs within a single WBDF system. This study synthesised SiO2 NPs from Halfaya bentonite clay waste and Al2O2 NPs from recycled aluminium scrap, char

Purpose: Current denture liner materials suffer from low tear strength, poor abrasion resistance, weak bond strength to denture material, and increasing risk of denture stomatitis due to adherence. The aim of this study was to evaluate the effects of the addition of cellulose nanofibers (CNFs) to commercial soft denture liner material on the adherence of and physical and mechanical properties. Materials and Methods: CNFs at concentrations of 0.0, 0.5, and 1.0 wt.% were incorporated into a soft liner material. Antifungal effects were assessed by quantifying the adherence of . The Shore A hardness, tensile strength, peel bond strength, and surface roughness tests were employed to assess the properties of the denture liner materials. Chemica

Background/Objectives: Early and accurate discrimination of neurological conditions, dementia, stroke and healthy aging, remains a critical clinical challenge. Electroencephalography (EEG) is a non-invasive measure of brain dynamics and entropy-based features obtained from multichannel EEG have shown strong discriminative ability. However, existing deep learning approaches do not sufficiently address the combined challenges of small clinical cohorts and high-dimensional entropy feature spaces. In this study, a novel architecture is proposed for multi-class neurological EEG classification under extreme small-sample conditions. Methods: A novel dual-branch Channel-wise Transformer and Attention-Branch Network (EEG-ChTABNet) are pr to