Background: Prostate cancer (PCa) is the most prevalent non-cutaneous malignancy and the second-leading cause of cancer-relatedmortality among males. Cancer is just one of the several disorders that may be linked to variations in trace element concentrations.Objective: To evaluate serum arrestin β-2 as a prostate cancer tumor marker and its association with trace elements.Methods: This case- control study was carried out at the Department of Biochemistry, College of Medicine, University of Baghdad and at the Urology department, Ghazi Al-Hariri Hospital for Surgical Specialities during the period from March 2022 to May 2023. In this case-control study 120 males were enrolled: Sixty men with newly diagnosed primary prostate cancer (P

Fifteen local isolates of Pseudomonas were obtained from several sources such as soil, water and some high-fat foods (Meat, olives, coconuts, etc.). The ability of isolates to produce lipase was measured by the size of clear zone on Tween 20 solid medium and by measuring the enzymatic activity and specific activity. Isolate M3 (as named in this study) was found to be the most efficient for the production of the lipase with enzymatic activity reached 56.6 U/ml and specific activity of 305.94 U/mg. This isolate was identified through genetic analysis of the 16S rRNA gene. and it was shown that the isolate M3 belongs to Pseudomonas aeruginosa with 99% similarity. The DNA of isolate M3 was extracted and lipase gene was amplified through PCR tec

Adverse drug reactions (ADR) are important information for verifying the view of the patient on a particular drug. Regular user comments and reviews have been considered during the data collection process to extract ADR mentions, when the user reported a side effect after taking a specific medication. In the literature, most researchers focused on machine learning techniques to detect ADR. These methods train the classification model using annotated medical review data. Yet, there are still many challenging issues that face ADR extraction, especially the accuracy of detection. The main aim of this study is to propose LSA with ANN classifiers for ADR detection. The findings show the effectiveness of utilizing LSA with ANN in extracting AD

Silicon nitride nanostructures were prepared by reactive sputtering technique using silicon targets with different types of electrical conductivity (n-type and p-type) and Ar:N2 gas mixing ratio of 70:30. The optical microscopy and spectroscopic characteristics of these films were determined in order to introduce the effect of target conductivity type on these characteristics. The results showed that using p-type silicon target would produce Si3N4 films with lower tendency to adsorb water vapor and other constituents of the atmospheric air, higher absorbance in the visible range 400-700nm, and lower variation in the energy band gap with film thickness than the Si3N4 films prepared from n-type silicon target.