Background: Acute myeloid leukemia (AML) is a genetically heterogeneous leukemia characterized by abnormal myeloid blast accumulation, disrupting normal hematopoiesis and leading to rapid progression. Objective: To investigate SNPs within the 3’UTR of the CCAAT/enhancer-binding protein alpha (CEBPA) gene and its association with AML in Iraqi patients. Methods: The study was carried out on 120 AML patients classified into newly diagnosed, induction chemotherapy, and consolidation chemotherapy stages (40 each), and 40 individuals as a control group. Genomic DNA was extracted from AML patients and controls, followed by PCR amplification and Sanger sequencing of the 3’UTR region of the CEBPA gene. The AML patients were characterized by age, sex, FMS-like tyrosine kinase 3 internal tandem duplication (FLT3-ITD), Nucleophosmin1 (NPM1) mutations, the French-American-British classification (FAB), and the World Health Organization (WHO). Results: The results revealed significant age differences among AML subgroups and notable hematological abnormalities, including reduced hemoglobin and platelet levels. According to the WHO classification, PML-RARA emerged as the most frequent fusion transcript. Based on FAB classification, M3 was the most common, followed by M4 and M0. The NPM1 mutations were more common than FLT3-ITD. The sequencing of the CEBPA 3′UTR region identified 83 variants, including 46 novel ones, 14 new forms of known SNPs, and 23 registered SNPs, reflecting substantial regulatory heterogeneity in this non-coding region. Conclusions: The CEBPA 3′UTR mutations reveal considerable genetic diversity among Iraqi AML patients, suggesting a potential regulatory role.
Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne
... Show MoreBipedal robotic mechanisms are unstable due to the unilateral contact passive joint between the sole and the ground. Hierarchical control layers are crucial for creating walking patterns, stabilizing locomotion, and ensuring correct angular trajectories for bipedal joints due to the system’s various degrees of freedom. This work provides a hierarchical control scheme for a bipedal robot that focuses on balance (stabilization) and low-level tracking control while considering flexible joints. The stabilization control method uses the Newton–Euler formulation to establish a mathematical relationship between the zero-moment point (ZMP) and the center of mass (COM), resulting in highly nonlinear and coupled dynamic equations. Adaptiv
... Show MoreBackground The appropriate disposal of medication is a well-recognized issue that has convened growing recognition in several contexts. Insufficient awareness relating to appropriate methods for the disposal of unneeded medicine may result in notable consequences. The current research was conducted among the public in Iraq with the aim of examining their knowledge, attitude, and practices regarding the proper disposal of unused and expired medicines. Methods The present study used an observational cross-sectional design that was community-based. The data were obtained from using an online questionnaire. The study sample included people of diverse genders, regardless of their race or occupational status. The study mandated that all pa
... Show MoreWe aimed to obtain magnesium/iron (Mg/Fe)-layered double hydroxides (LDHs) nanoparticles-immobilized on waste foundry sand-a byproduct of the metal casting industry. XRD and FT-IR tests were applied to characterize the prepared sorbent. The results revealed that a new peak reflected LDHs nanoparticles. In addition, SEM-EDS mapping confirmed that the coating process was appropriate. Sorption tests for the interaction of this sorbent with an aqueous solution contaminated with Congo red dye revealed the efficacy of this material where the maximum adsorption capacity reached approximately 9127.08 mg/g. The pseudo-first-order and pseudo-second-order kinetic models helped to describe the sorption measure