Background: Polycystic ovary syndrome is a heterogeneous disorder and its etiology appears to be complex and multifactorial; characterized by hyperandrogenism, chronic anovulation and infertility. It’s associated with evidence of low-grade chronic inflammation, as indicated by the presence of elevated levels of high sensitive C- reactive protein levels, interleukin-6 and tumor necrosis factor-α. The source of excess circulating tumor necrosis factor-α in obese Polycystic ovary syndrome patient is likely to be the adipose tissues while in lean women increased visceral adiposity has been proposed as a source of excess tumor necrosis factor-α.Objectives: to evaluate the levels of high sensitive C- reactive protein, tumor necrosis factor-α and interleukin-6 in patients with polycystic ovary syndrome before and after treatment with metformin; with emphasis on their relationship with the improvement in ovulation rate and body mass index in Iraqi women.Methods: 69 Iraqi females with PCOS, with mean age of 25.8±4.4 years, body mass index 31.14±2.23 kg/m2 and insulin resistant equal to 3.15±0.25. Additionally, 30 healthy fertile women BMI= 26.87±3.1 kg/m2 and mean age 23.4±2.8 years), the patients were treated with metformin 1500 mg/day for 3 months. Blood samples were obtained in the morning subsequent to an overnight fasting at baseline and at the end of the 12 weeks period of treatment, the samples were analyzed for plasma glucose level estimated by enzymatic colorimetric kit, while serum insulin , TNF-α, IL-6 , hs-CRP, Progesterone and sex hormone binding globulin . Results: BMI values were significantly increased at baseline value in patients (P<0.05) compared with healthy controls, then significantly decreased (12.9%) after treatment compared with baseline values, HOMA-IR index were significantly elevated in patients group at baseline compared with control, and significantly decreased by 17.4% after treatment. Regarding the influence of metformin on inflammatory markers, the present study demonstrated significant elevation of baseline levels (P<0.05) of TNF-α, hs-CRP and IL-6 compared with controls, and the baseline levels significantly decreased after treatment by 16%, 38% and 37% respectively. Meanwhile, sex hormone binding globulin levels were significantly decreased in PCOS patients compared with healthy controls, and significantly increased after treatment by 16.6%, also progesterone levels decline at baseline compared with control group, and it was increased significantly after treatment by 24%.Conclusions: The study detects an increased level of inflammatory cytokines, SHBG and decrease level of progesterone in Iraqi females with PCOS, and metformin therapy improves serum levels of the inflammatory cytokines associated with increased ovulation rate.
We 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
Little is known about hesitancy to receive the COVID‐19 vaccines. The objectives of this study were (1) to assess the perceptions of healthcare workers (HCWs) and the general population regarding the COVID‐19 vaccines, (2) to evaluate factors influencing the acceptance of vaccination using the health belief model (HBM), and (3) to qualitatively explore the suggested intervention strategies to promote the vaccination.
This was a cross‐sectional study based on electronic survey data that was collected in Iraq during December first‐19th, 2020. The electronic surve
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 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 MorePushover analysis is an efficient method for the seismic evaluation of buildings under severe earthquakes. This paper aims to develop and verify the pushover analysis methodology for reinforced concrete frames. This technique depends on a nonlinear representation of the structure by using SAP2000 software. The properties of plastic hinges will be defined by generating the moment-curvature analysis for all the frame sections (beams and columns). The verification of the technique above was compared with the previous study for two-dimensional frames (4-and 7-story frames). The former study leaned on automatic identification of positive and negative moments, where the concrete sections and steel reinforcement quantities the
... 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 More