Introduction: Selenium is an essential trace element involved in different physiological functions of the human body. An inverse relationship between serum selenium levels and cervical intraepithelial neoplasia has been reported. cervical intraepithelial neoplasia is regarded as a potentially premalignant transformation of squamous cells of the cervix. Objectives: To evaluate the relationship between the serum level of selenium and cervical intraepithelial neoplasia. Methods: A case-control study was conducted at Baghdad Teaching Hospital and Iraqi National Cancer Research Center in the University of Baghdad during the period from July 2021 to July 2022. A convenient sample of 100 women was enrolled in the current study and included

ABSTRACT : Alzheimer’s disease (AD) is one of the most common inflammatory neurodegenerative diseases linked with dementia, it is characterized by the deposition of amyloid beta-peptide (Ab) in the brain. The present study aims to innovate a biochemical relationship between AD and interleukin 38 (IL-38) as an anti-inflammatory cytokine, expose novel mechanisms and concepts regarding other biochemical parameters studied previously or recently in AD patients and also examine the biochemical action of memantine (10 mg daily) on AD patients. Sixty (60) diagnosed AD patients participated in the present study and classified into four (4) groups: G3 were composed of (15) newly diagnosed males (52-78) years / without treatment, G4 composed of (15

The method of predicting the electricity load of a home using deep learning techniques is called intelligent home load prediction based on deep convolutional neural networks. This method uses convolutional neural networks to analyze data from various sources such as weather, time of day, and other factors to accurately predict the electricity load of a home. The purpose of this method is to help optimize energy usage and reduce energy costs. The article proposes a deep learning-based approach for nonpermanent residential electrical ener-gy load forecasting that employs temporal convolutional networks (TCN) to model historic load collection with timeseries traits and to study notably dynamic patterns of variants amongst attribute par

In this paper, an algorithm is suggested to train a single layer feedforward neural network to function as a heteroassociative memory. This algorithm enhances the ability of the memory to recall the stored patterns when partially described noisy inputs patterns are presented. The algorithm relies on adapting the standard delta rule by introducing new terms, first order term and second order term to it. Results show that the heteroassociative neural network trained with this algorithm perfectly recalls the desired stored pattern when 1.6% and 3.2% special partially described noisy inputs patterns are presented.

Background: Hypothyroidism is the most abundant thyroid disorder worldwide. For decades, levothyroxine was the main effective pharmacological treatment for hypothyroidism. A variety of factors can influence levothyroxine dose, such as genetic variations. Studying the impact of genetic polymorphisms on the administration of medications was risen remarkably. Different genetic variations were investigated that might affect levothyroxine dose requirements, especially the deiodinase enzymes.  Deiodinase type 2 genetic polymorphisms’ impact on levothyroxine dose was studied in different populations. Objective: To examine the association of the two single nucleotide polymorphism (SNP)s of deiodinase type 2 (rs225013 and rs225014) and le

Background: Dysfunction of sinoatrial node is a set of abnormal rhythms which are resulted from the sinoatrial node malfunctionof the sinus node, the chief natural cardiac pacemaker. The common, and occasionally, the single method for treatment of heart arrhythmias wasimplantation of pacemaker, which reduce symptoms exactly occurs after implantation. Aim: To detect the association between red cell width diameter (RDW) and some cardiac electrophysiology parameters in sinus node dysfunction in Iraqi patients such as SNRT and AH. Methods: A cross sectional study, was conducted on 59 patient ranging between 20-50 years old and involving 35 female and 24 male patients, suffering from an unexplained symptoms of sinoatrial node dysfunction (SND).

Background: Hypothyroidism is the most abundant thyroid disorder worldwide. For decades, levothyroxine was the main effective pharmacological treatment for hypothyroidism. A variety of factors can influence levothyroxine dose, such as genetic variations. Studying the impact of genetic polymorphisms on the administration of medications was risen remarkably. Different genetic variations were investigated that might affect levothyroxine dose requirements, especially the deiodinase enzymes.  Deiodinase type 2 genetic polymorphisms’ impact on levothyroxine dose was studied in different populations.

Objective: To examine the association of the two single nucleotide polymorphism (SNP)s of deiodinase t