Background: Treatment modalities of acromegaly and disease control impact differently on glucose homeostasis and lipid changes, and consequently on cardiometabolic risk. Aim: To investigate the possible association of lipid profile changes with the glycemic control status in acromegaly patients treated with octreotide LAR. Methods: This cross-sectional study included 52 Iraqi patients with acromegaly treated with octreotide LAR and not using statins. Demographic, anthropometric, and clinical data were collected, as well as the duration of Octreotide LAR administration. The glycemic state was assessed and classified as DM, prediabetes, or normal. Plasma levels of triglycerides, LDL cholesterol, HDL cholesterol, and non-HDL were evalu

Inflammation of the tonsils could be described as acute tonsillitis, mainly due to infection. Recurrent tonsillitis could be defined as 3-7 episodes during the first 3 years of age. Vitamin D, which is a neuro-hormone with pleiotropic biological activities may modulate the immune response by alleviation, and stimulation of Th1 and Th2 cell proliferation, respectively, that influence the stimulation, synthesis, and secretion of both pro and anti-inflammatory cytokines. In this study we aimed to shed light on the levels of vitamin D in children with different episodes of tonsillitis in association with levels of interleukins (TNFα, IL-2, IL-4, IL-10). Blood samples were collected from 48 participants in 3 groups: control, acute tonsilliti

Interleukin -33 is a new member of the IL-1 superfamily of cytokines that is expressed mainly by stromal cells.Its expression is upregulated following pro-inflammatory stimulation.Aim of the present study was to assess the serum IL-33 level and its relationship with inflammatory biomarker CRP in Iraqi females patients with celiac disease. Thirty five patients with celiac disease (CD) and thirty healthy individuals as control group were enrolled in this study,their age ranged (20-35) year.Anti-Gliadin IgA ,IgG and Anti-Tissue IgA ,IgG were estimated in all subjects as diagnostic parameters .ESR and CRP were assayed as inflammatory biomarkers. IL-33 was determined in patients and control groups.The results of the present study revealed a hig

Objectives: The research aims to demonstrate the integration between Quantum Computing (QC) and Predictive Analysis (PA) and their role in reducing costs while achieving Sustainable Development Goals (SDGs). The study addresses the inefficiencies in calculating and measuring product costs under traditional systems and examines how QC and PA can enhance cost reduction and product quality to better meet customer needs. Additionally, the research seeks to strengthen the theoretical framework with practical applications, illustrating how this integration improves a company’s competitive position while promoting social, environmental, and economic sustainability.   Methods: The study employs a descriptive analytical approach, focusi

This research aims to explore the status effects of the Sudden, and gradual of AI-Driven Cyber Security (AIDC), Big data analytics and Business Intelligence (BI) The strategic flexibility (SF) and entrepreneurship (ENT) on Iraqi internet services providers ISPs. The work fills an important lacunae in what the advanced dimensions of technology have with regard to its influencing both SF and ENT outcomes in developing economy context, where empirical evidences are scant. A cross-sectional survey based on a quantitative research methodology was conducted on 113 professionals in Iraqi telecommunication sector. A partial least squares structural equation modeling (PLS-SEM) approach was adopted to examine 10 hypotheses concerning the relationship

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