The aim of this study was to critically appraise and synthesize the best available evidence on the effectiveness of interventions suitable for delivery by nurses, designed to enhance cardiac patients' adherence to their prescribed medications.

Background: The finite element method (FEM) is expected to be one of the most effective computational tools for measuring the stress on implant-supported restorations. This study was designed using the 3D-FEM to evaluate the effect of two adhesive luting types of cement on the occlusal stress and deformation of a hybrid crown cemented to a mono-implant. Materials and Method: The mono-screw STL file was imported into the CAD/CAM system library from a database supported by De-Tech Implant Technology. This was to assist in the accurate reproduction of details and design of a simulated implant abutment. Virtually, a digital crown was designed to be cemented on an abutment screw. A minimum occlusal thickness of 1mm and marginal fitting of 1.2

Hormones, their receptors, and the associated signaling pathways make compelling drug targets because of their wide-ranging biological significance to study the role of asprosin in obese male patients with diabetic mellitus type II. ELISA method was used to assay asprosin and insulin. Blood was taken with drawn sample from 30 obese normal patients with age range (40-60) years, 30 diabetic patients with age range (40-60) years at duration of disease (1-5) years and 30 normal healthy patients. The mean difference between T2DM according to insulin % (23.8±0.6) was increased than the mean of IFG (17.7±1.0) (P 0.000). The mean difference between T2DM according to asprosin (122.1±21.8) was increased than the mean of IFG (51.4±2.7) (P 0

Recently, it has been revealed that Toxoplasmosis may be associated with some factors related to type 2 diabetes, such as glucose, insulin, the Homeostatic Model Assessment for Insulin Resistant (HOMA-IR), and Fatty acid binding protein (FABP). Therefore, the current study aimed to specify how Toxoplasma gondii (T.gondii) infection affects glucose, insulin, HOMA-IR, and FABP among adolescents. From October to December 2022, this study was carried out at Al Madain Hospital in Baghdad. For a group of adolescents visiting the hospital, an ELISA test was performed to check their anti-T.gondii antibodies. Ninety adolescents were selected to participate in the study on the basis of this examination. They were divided into two groups: those who te

In this paper, we proved that if R is a prime ring, U be a nonzero Lie ideal of R , d be a nonzero (?,?)-derivation of R. Then if Ua?Z(R) (or aU?Z(R)) for a?R, then either or U is commutative Also, we assumed that Uis a ring to prove that: (i) If Ua?Z(R) (or aU?Z(R)) for a?R, then either a=0 or U is commutative. (ii) If ad(U)=0 (or d(U)a=0) for a?R, then either a=0 or U is commutative. (iii) If d is a homomorphism on U such that ad(U) ?Z(R)(or d(U)a?Z(R), then a=0 or U is commutative.

Background and Objectives: Urinary tract infections (UTIs), among a wide range of microbial infections, are of a double-edged worry with health-care and economic implications. They are serious diseases that can influence various parts of the urinary tract. The aim of this study was characterization of the enteric bacteria isolated from urine of human UTIs and studying their antimicrobial sensitivity. Materials and methods: A total of 50 urine samples were collected from patients with UTIs of both genders. The isolates identification was done using routine diagnostic methods and confirmed by Vitek2. Antimicrobial susceptibility was done against 10 antimicrobials. Results: Both genders of human were found to suffer from urinary tract problems

Offline handwritten signature is a type of behavioral biometric-based on an image. Its problem is the accuracy of the verification because once an individual signs, he/she seldom signs the same signature. This is referred to as intra-user variability. This research aims to improve the recognition accuracy of the offline signature. The proposed method is presented by using both signature length normalization and histogram orientation gradient (HOG) for the reason of accuracy improving. In terms of verification, a deep-learning technique using a convolution neural network (CNN) is exploited for building the reference model for a future prediction. Experiments are conducted by utilizing 4,000 genuine as well as 2,000 skilled forged signatu