The aim of the present study was to demonstrate the possible role of statins on the inflammatory biomarkers in patients with periodontal disease (PD) This cross-sectional study involved 74 patients with PD and/or dyslipidemia divided into Group A: 34 patients with PD (nonstatins users); Group B: 40 patients with PD (statins users); and Group C: 30 healthy controls. Total cholesterol (TC), triglyceride (TG) and high-density lipoprotein, C-reactive protein (CRP), interleukin-6 (IL-6), tumor necrosis factor alpha (TNF-α), and malondialdehyde (MDA) were measured . Blood pressure prolife and indices of PD were evaluated in each group. Statistical analysis was conducted by using SPSS version 20.0.

The current study was designed to investigate the impact of the missense Single Nucleotide Polymorphism (SNP), Asn291Ser (c.872A>G: rs12470652), of LHR gene (Luteinizing hormone receptor gene) in peripheral blood samples of Iraqi infertile women diagnosed with premature ovarian failure (POF) and normosmic idiopathic hypogonadotropic hypogonadism(niHH, patients with normal sense of smell). Following the hormonal analysis, fifty women diagnosed with premature ovarian failure and fifty women diagnosed with normosmic idiopathic hypogonadotropic hypogonadism were included as patient groups, while fifty healthy fertile women were enrolled as a control group. The blood samples were obtained from patient and control groups at Kamal Al-Samarra

Thyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid dise

In this study, a one-dimensional model represented by Butler-Volmer-Monod (BVM) model was proposed to compute the anode overpotential and current density in a mediator-less MFC system. The system was fueled with various organic loadings of real field petroleum refinery oily sludge to optimize the favorable organic loading for biomass to operate the suggested system. The increase in each organic loading showed higher resistance to electrons transport to the anode represented by ohmic loss. On the contrary, both activation and mass transfer losses exhibited a noticeable decrement upon the increased organic loadings. However, current density was improved throughout all increased loads achieving a maximum current density of 5.2 A/m³

In the field of civil engineering, the adoption and use of Falling Weight Deflectometers (FWDs) is seen as a response to the ever changing and technology-driven world. Specifically, FWDs refer to devices that aid in evaluating the physical properties of a pavement. This paper has assessed the concepts of data processing, storage, and analysis via FWDs. The device has been found to play an important role in enabling the operators and field practitioners to understand vertical deflection responses upon subjecting pavements to impulse loads. In turn, the resultant data and its analysis outcomes lead to the backcalculation of the state of stiffness, with initial analyses of the deflection bowl occurring in conjunction with the measured or assum

Coronavirus disease (COVID-19) is an acute disease that affects the respiratory system which initially appeared in Wuhan, China. In Feb 2019 the sickness began to spread swiftly throughout the entire planet, causing significant health, social, and economic problems. Time series is an important statistical method used to study and analyze a particular phenomenon, identify its pattern and factors, and use it to predict future values. The main focus of the research is to shed light on the study of SARIMA, NARNN, and hybrid models, expecting that the series comprises both linear and non-linear compounds, and that the ARIMA model can deal with the linear component and the NARNN model can deal with the non-linear component. The models

        In this paper, the necessary optimality conditions are studied and derived for a new class of the sum of two Caputo–Katugampola fractional derivatives of orders (α, ρ) and( β,ρ) with fixed the final boundary conditions. In the second study, the approximation of the left Caputo-Katugampola fractional derivative was obtained by using the shifted Chebyshev polynomials. We also use the Clenshaw and Curtis formula to approximate the integral from -1 to 1. Further, we find the critical points using the Rayleigh–Ritz method. The obtained approximation of the left fractional Caputo-Katugampola derivatives was added to the algorithm applied to the illustrative example so that we obtained the approximate results for the stat

This study is pointed out to estimate the effectiveness of two solvents in the extraction and evaluating the active ingredients and their antioxidant activity as well as anti-cancer efficiency. Therefore, residues from four different Brassica vegetables viz. broccoli, Brussels sprout, cauliflower, and red cherry radish were extracted using two procedures methods: methanolic and water crude extracts. Methanol extracts showed the highest content of total phenolic (TP), total flavonoids (TF), and total tannins (TT) for broccoli and Brussels sprouts residues. Methanolic extract of broccoli and Brussels sprouts residues showed the highest DPPH· scavenging activity (IC₅₀ = 15.39 and 18.64 µg/ml). The methanol and water ex

Type 2 Diabetes Mellitus (T2DM) is the furthermost common form of DM which is identified by hyperglycemia, insulin resistance, and relative insulin deficiency. This study aims to detect the role of interleukin-17 (IL-17) in patients with T2DM compared with the healthy control and to investigate the relationship between IL-17 and insulin resistance. The study involved 50 Iraqi T2DM patients, randomly selected with an age range of 33-71 years .For the purpose of comparison, 30 Iraqi healthy persons with an age range of 33-71 years were also included. Patients and control groups were characterized in terms of gender, age, body mass index (BMI), homeostatic model assessment-insulin resistance(HOMA-IR),fasting serum glucose (FSG) and lipid pr