Salivary peroxidases have biological functions of particular importance to oral health. The aim of this paper is to shed the light on saliva and serum total peroxidases activity as well as the activity of each of salivary peroxidase (SPO) and myeloperoxidase (MPO) in patients with oral tumors. The studied participants were divided into two groups: the first group included 18 oral squamous cell carcinoma patients and 20 age and gender-matched healthy controls while the second group consisted of 20 oral ossifying fibroma patients and 23 age and gender-matched healthy controls. Total peroxidases activity was determined, and its specific activity was calculated in serum and whole mixed saliva as well as in the supernatant and pellet fractions

Background: coronavirus 19 is a beta-coronavirus, enveloped and roughly spherical with approximately 60 to 140 nm in diameter with positive-sense single-stranded RNA genome.

Objectives: Measurement of interleukin 6 (IL6) level in a group of patients with confirmed Covid19 infection and its correlation with many hematological and  biochemical parameters , mainly lymphocyte , neutrophil  count and their ratio , platelet count , serum ferritin , C reactive protein as well as D-dimer level

Subjects and Methods: This study was conducted on 60 PCR positive patients variably affected by COVID-19 , cases collected sequentially from June till November 20

Statisticians often use regression models like parametric, nonparametric, and semi-parametric models to represent economic and social phenomena. These models explain the relationships between different variables in these phenomena. One of the parametric model techniques is conic projection regression. It helps to find the most important slopes for multidimensional data using prior information about the regression's parameters to estimate the most efficient estimator. R algorithms, written in the R language, simplify this complex method. These algorithms are based on quadratic programming, which makes the estimations more accurate.

Twelve species from Brassicaceae family were studied using two different molecular techniques: RAPD and ISSR; both of these techniques were used to detect some molecular markers associated with the genotype identification. RAPD results, from using five random primers, revealed 241 amplified fragments, 62 of them were polymorphic (26%).

    ISSR results showed that out of seven primers, three (ISSR3, UBC807, UBC811) could not amplify the genomic DNA; other primers revealed 183 amplified fragments, 36 of them were polymorphic (20%). The similarity evidence and dendrogram for the genetic distances of the incorporation between the two techniques showed that the highest similarity was 0.897 between the va

The aim of this research is to demonstrate the impact of credit risk on the banks of the study sample on the granting of loans and credit facilities, and try to reduce the size of credit risk to banks as a result of granting loans and credit facilities, credit risk is the oldest form of risk in financial markets. Every financial institution takes a degree of risk when it gives loans and credit facilities to companies and customers, It is exposed to financial losses when some borrowers fail to repay their loans as agreed, and at the same time credit facilities are the most profitable operations of the bank as it is the most profitable banking operations than other operations, so it represents the research communit

Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a

CD40 is a type 1 transmembrane protein composed of 277 amino acids, and it belongs to the tumor necrosis factor receptor (TNFR) superfamily. It is expressed in a variety of cell types, including normal B cells, macrophages, dendritic cells, and endothelial cells, as a costimulatory molecule. This study aims to summarize the CD40 polymorphism effect and its susceptibility to immune-related disorders. The CD40 gene polymorphisms showed a significant association with different immune-related disorders and act as a risk factor for increased susceptibility to these diseases.

Determination of the concentrations of some inorganic elements (Fe, Co, Cu, Cr, Ni, Pb, Cd) by Flame Atomic Absorption Spectroscopy, Electrothermal Atomic Absorption Spectroscopy, and Inductively Coupled Plasma. and two dangerous organic pollutants (PAH and phenols) by GC and UV in the wastewater of Z.LTF Zafaraniya Leather tanning factory, W.BF Al-Waziriya Battery factory, Ba.WLS Al-Bayaa Wastewater Lifting Station, and some points of Tigris River in Baghdad city taking into consideration the sampling time Varying (two months) and setting the temperature during the drawing of the model. The results of the analysis revealed that the wastewater was contaminated with phenols, PAHs, and metals (Pb, Cd, Cr, Cu) at high rates that exceeded the p